1. Description

This R Markdown document describes the analyses performed for the manuscript entitled “Environmental pollution correlates with parasite infection across a riverine landscape” by Io S. Deflem, Seppe Marchand, Federico C.F. Calboli, Joost A.M. Raeymaekers, Filip A.M. Volckaert and Pascal I. Hablützel.

The analyses were run in R 4.1.2

2. Study area and sampling

Up to thirty 0+ three-spined sticklebacks were sampled at 37 locations in the Dijle and Demer basins in Belgium during autumn 2016 under a permit of the Flemish Agency Nature and Forest (Fig. 1). Both basins together cover a continuous surface area of 3,624 km² with the furthest two sampling sites being located 117 km apart (distance measured along rivers). All locations included small and relatively slow flowing streams (drop off from highest to lowest point is 18 m) covering a wide range of ecological, hydromorphological, and physico-chemical characteristics. Fish were caught using a dip net.

3. Setting up working environment

# Empty environment
rm(list=ls())

# Set working directory to location where script is stored
setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) # requires installation of package "rstudioapi"

4 Loading and preparing host and parasite data

Fish were euthanized with a lethal dose of MS222 on the day of capture, following directions of the KU Leuven Animal Ethics Commission, and stored at -20 °C. Fish were kept in separate containers per site at all times. Lab based parasite screening of thawed fish involved placing individual fish in 5 or 10 ml cryo-tubes with 1 or 2 ml of distilled water. Following a vigorous shake of 10 s, the liquid was poured into a Petri dish and ectoparasites were identified and counted using a stereomicroscope. Fish were rinsed and checked again for the presence of ectoparasites on skin and fins. The intestines were examined for endoparasites. Before dissection, fish weight (± 0.1 mg) and standard length (± 1 mm) were recorded. To quantify body condition, we calculated the scaled mass index (SMI; Maceda-Veiga et al., 2014; Peig & Green, 2009). Sex was determined during dissection by inspection of gonad development. A total of 668 fish were dissected, which amounts to approximately 20 fish per location, with the exception of seven locations where only 10 fish were screened for the presence of macroparasites. Ecto- and endoparasites were morphologically identified to species level whenever possible.

# Parasite data
data <- read.csv("data_2016_2303.csv", sep=';')
data$site <- as.factor(data$site)

# Calculate parasite parameters
names(data)
##  [1] "site"                "fish"                "parspeciesrichness" 
##  [4] "div_shannon"         "div_simpson"         "temp"               
##  [7] "pH"                  "conductivity"        "nitrogen"           
## [10] "phosphorus"          "oxygen"              "netcen"             
## [13] "updist"              "updist2"             "updist3"            
## [16] "fishspeciesrichness" "weight"              "weigh..g."          
## [19] "length"              "SMI"                 "Sex"                
## [22] "Gyr"                 "Tri"                 "Glu"                
## [25] "ecto_screener"       "Con"                 "CysL"               
## [28] "Pro"                 "Aca"                 "Cam"                
## [31] "Ang"                 "CysI"                "endo_screener"      
## [34] "PI"                  "PI_ecto"             "PI_endo"
#parasite data is overdispersed (mostly so for Trichodina), if using average abundance data, species matrix needs to be transformed
datao <- na.omit(data[,c(1,22:24,26:32)]) #remove fish without parasite counts

library(vegan)
## Loading required package: permute
## Loading required package: lattice
## This is vegan 2.6-4
ddata <- dispweight(datao[,-1]) #correct for overdispersion of the parasite count data
avab <- aggregate(ddata, by = list(datao[,1]), function(x){mean(x, na.rm =T)})
prev = aggregate(data[,c(22:24,26:32)], by = list(data[,1]), function(x){sum(x >0, na.rm = T)/length(x)})
medin = aggregate(data[,c(22:24,26:32)], by = list(data[,1]), function(x){median(x[x >0], na.rm = T)}) 
pa = aggregate(data[,c(22:24,26:32)], by = list(data[,1]), function(x){ifelse(mean(x, na.rm =T)>0,1,0)}) 

avab[is.na(avab)] <- 0
prev[is.na(prev)] <- 0
medin[is.na(medin)] <- 0

# Host condition data
avcondition <- aggregate(data$SMI, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]
avlength <- aggregate(data$length, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]

# Parasite index
sgyr <- 1:nrow(data)
stri <- 1:nrow(data)
sglu <- 1:nrow(data)
scon <- 1:nrow(data)
scysl <- 1:nrow(data)
spro <- 1:nrow(data)
saca <- 1:nrow(data)
scam <- 1:nrow(data)
sang <- 1:nrow(data)

for(j in 1:nrow(data)){
  sgyr[j] <- data$Gyr[j]/sd(data$Gyr, na.rm=T)
  stri[j] <- data$Tri[j]/sd(data$Tri, na.rm=T)
  sglu[j] <- data$Glu[j]/sd(data$Glu, na.rm=T)
  scon[j] <- data$Con[j]/sd(data$Con, na.rm=T)
  scysl[j] <- data$CysL[j]/sd(data$CysL, na.rm=T)
  spro[j] <- data$Pro[j]/sd(data$Pro, na.rm=T)
  saca[j] <- data$Aca[j]/sd(data$Aca, na.rm=T)
  scam[j] <- data$Cam[j]/sd(data$Cam, na.rm=T)
  sang[j] <- data$Ang[j]/sd(data$Ang, na.rm=T)
}

PI <- 1:nrow(data)
for(j in 1:nrow(data)){
  PI[j] <- 10/max(sgyr, na.rm=T)*sgyr[j] + 10/max(stri, na.rm=T)*stri[j] + 10/max(sglu, na.rm=T)*sglu[j] +
    10/max(scon, na.rm=T)*scon[j] + 10/max(scysl, na.rm=T)*scysl[j] + 10/max(spro, na.rm=T)*spro[j] +
    10/max(saca, na.rm=T)*saca[j] + 10/max(scam, na.rm=T)*scam[j] + 10/max(sang, na.rm=T)*sang[j]
}

PI_ecto <- 1:nrow(data)
for(j in 1:nrow(data)){
    PI_ecto[j] <- 10/max(sgyr, na.rm=T)*sgyr[j] + 10/max(stri, na.rm=T)*stri[j] + 10/max(sglu, na.rm=T)*sglu[j]
}

PI_endo <- 1:nrow(data)
for(j in 1:nrow(data)){
  PI_endo[j] <-     10/max(scon, na.rm=T)*scon[j] + 10/max(scysl, na.rm=T)*scysl[j] + 10/max(spro, na.rm=T)*spro[j] +
    10/max(saca, na.rm=T)*saca[j] + 10/max(scam, na.rm=T)*scam[j] + 10/max(sang, na.rm=T)*sang[j]
}

avPI <- aggregate(PI, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]
avPI_ecto <- aggregate(PI_ecto, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]
avPI_endo <- aggregate(PI_endo, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]

5 Loading and preparing environmental and spatial data

Physico-chemical data was provided by the Flemish Environmental Agency (VMM). Each fish sampling site was chosen at or near an environmental monitoring site of VMM. Water parameters include water temperature, pH, conductivity, dissolved oxygen (O2), saturation with dissolved oxygen, and Biochemical and Chemical Oxygen Demand (BOD and COD). Nutrient related water parameters include measurements of nitrate (NO3-), nitrite (NO2-), Kjeldahl nitrogen (KjN), total nitrogen (Nt), ammonium (NH4+), and total phosphorus (Pt). Following removal of strong collinear variables (significant correlation with P < 0.05 and Pearson correlation coefficient > |0.6|; Dormann et al., 2013), six environmental physico-chemical variables were retained (temperature, conductivity, COD, saturation with dissolved oxygen, ammonium, and total nitrogen), representing different aspects of water quality. For each water parameter, the average value of the year before sampling was calculated based on monthly monitoring data. Additionally, two hydromorphological variables were included: Tthe presence of a pool-riffle pattern and meanders were noted during field sampling and these parameters were included as binary variables (presence/absence) for a representation of abiotic habitat structure. Spatial (waterway) distances were calculated using the Network Analyst toolbox in ArcGIS. Upstream distance was defined as the maximal upstream distance from the sampling location. Network peripherality was calculated as the average waterway distance of a sampling location to all other locations. Hence, a total of eight environmental and two spatial variables were included in the statistical analysis.

# Environmental data (VMM)
environment <- read.csv("Environment_update.csv", sep=';')
spavar <- read.csv("space2.csv", sep=';') #spatial variables: network centrality and upstream distance
plot(spavar$netcen); plot(density(spavar$netcen))

plot(spavar$updist); plot(density(spavar$updist))

#environmental data (from field observations)
field_data <- read.csv("field_data.csv", sep=',')
environment2 <- cbind(environment[,c(1,49,52:53,55,57,60,63)], field_data[-c(8,10,25,27,37),33:34], spavar[,c(2,3)])
environment2$pool_riffle <- as.factor(environment2$pool_riffle)
environment2$meander <- as.factor(environment2$meander)

netcen <- spavar$netcen
updist <- spavar$updist

We used univariate generalized linear models to investigate how landscape-level effects modify infection patterns of individual parasite taxa, host size and condition. We kept the statistical models linear (as opposed to polynomial) and only considered main effects (i.e. no interaction terms) because we had no prior information from this study system that more complex models were necessary and because the study design with (only) 37 sampling sites was not intended for non-linear models. Ten explanatory variables (temperature, conductivity, COD, saturation with dissolved oxygen, ammonium, total nitrogen, the presence of pool-riffle patterns and meanders, upstream distance, and network peripherality) were included.

6. Univeriate analysis using Bayesian Model Averaging

Univariate analyses - We used generalized linear models in a BMA approach to understand how infection with individual parasite taxa relate to host characteristics (length and condition), environmental conditions as well as spatial distance among sampling sites. Parasite infection was calculated in three ways at the host population level: average abundance (mean parasites per host), prevalence (percentage of infected hosts) and median infection intensity (median number of parasites in infected hosts). We calculated the individual parasitation index (IPI) following Kalbe et al. (2002) as a measurement for total parasite abundance and species richness for each individual fish. This index was calculated for all parasite species combined, and for ecto- and endoparasite species separately. For these models, we assumed a normal error distribution (which appeared to be justified, see Supplementary Figures S1-S2) and applied a Jeffrey-Zellner-Siow prior. Model assumptions (homoscedasticity of the variances and normal distribution of the errors) were assessed using the generic model plot function in R and did onlynot clearly deviate in any of the models for rare parasites. We followed a normal distribution, and not Poisson or negative binomial, for the parasite data for the common species (Trichodina sp. and Gyrodactylus spp.) and the individual parasitation index as the parameters used are deviates from count data. Rare parasites (Glugea, Contracaecum, Anguillicoloides, and unidentified cysts) were excluded from the univariate analysis because there was not enough data to obtain a good fit of the models.For rare parasites (Contracaecum sp. and Anguillicoloides crassus), we used population-level presence-absence data assuming a binomial error distribution and a uniformly distributed BIC prior. Due to low prevalences, the other parasites were not included in the species-specific models. Explanatory variables were considered important when they had a posterior inclusion probability (PIP) of 0.5. To account for overdispersion in the parasite counts, we transformed the data by downweighting overdispersed taxa following Clarke et al. (2006) using the dispweight function in the R package vegan v2.5.6 (Oksanen et al., 2013).

6.0.1 Figure

library(BAS)

# Make a matrix for PIP (Posterior Inclusion Probability)
PIP <- matrix(nrow=12, ncol=14)
rownames(PIP) <- c("Host condition", "Host size", "Temperature", "Oxygen saturation", "Conductivity", "COD", "Ammonium", "Total nitrogen", "Pool riffle pattern", "Meander", "Network peripherality", "Upstream distance")
colnames(PIP) <- c("Host condition", "Host size", "Gyrodactylus abundance", "Gyrodactylus prevalence", "Gyrodactylus infection intensity", "Trichodina abundance", "Trichodina prevalence", "Trichodina infection intensity", "Glugea", "Contracaecum", "Aguillicola",
                   "PI", "PI ecto", "PI endo")  
#Condition
bas.model <- bas.lm(avcondition ~ T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(3:12),1] <- pip[2:11,1]*sign(coef.model$postmean[2:11])

#Length
bas.model <- bas.lm(avlength ~ T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(3:12),2] <- pip[2:11,1]*sign(coef.model$postmean[2:11])

#Gyrodactylus abundance
bas.model <- bas.lm(avab$Gyr ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Gyrodactylus prevalence
bas.model <- bas.lm(prev$Gyr ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),4] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Gyrodactylus infection intensity
bas.model <- bas.lm(medin$Gyr ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),5] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Trichodina abundance
bas.model <- bas.lm(avab$Tri ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),6] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Trichodina prevalence
bas.model <- bas.lm(prev$Tri ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),7] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Trichodina infection intensity
bas.model <- bas.lm(medin$Tri ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),8] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Glugea
bas.model <- bas.glm(pa$Glu ~  avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, betaprior=g.prior(100), family=binomial)
coef.model <- coef(bas.model)
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 220 > 1'
## in coercion to 'logical(1)'

## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 220 > 1'
## in coercion to 'logical(1)'
pip <- summary(bas.model)
PIP[c(1:12),9] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Contracaecum
bas.model <- bas.glm(pa$Con ~  avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, betaprior=g.prior(100), family=binomial)
coef.model <- coef(bas.model)
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 234 > 1'
## in coercion to 'logical(1)'
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 234 > 1'
## in coercion to 'logical(1)'
pip <- summary(bas.model)
PIP[c(1:12),10] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#Anguillicola
bas.model <- bas.glm(pa$Ang ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, betaprior=g.prior(100), family=binomial)
coef.model <- coef(bas.model)
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 371 > 1'
## in coercion to 'logical(1)'
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 371 > 1'
## in coercion to 'logical(1)'
pip <- summary(bas.model)
PIP[c(1:12),11] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#PI
bas.model <- bas.lm(avPI ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),12] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#PI ecto
bas.model <- bas.lm(avPI_ecto ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),13] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

#PI endo
bas.model <- bas.lm(avPI_endo ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
coef.model <- coef(bas.model)
pip <- summary(bas.model)
PIP[c(1:12),14] <- pip[2:13,1]*sign(coef.model$postmean[2:13])
library(gplots)
## 
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
## 
##     lowess
x = round(PIP, digits=2)
x[abs(PIP)<0.5] <- ""
x[abs(PIP)>0.5] <- "+"
heatmap.2(PIP[,-c(9,10,11)],
          cellnote = x[,-c(9,10,11)],
          #main = "Correlation",
          notecex=1,
          notecol="white",
          density.info="none",
          trace="none",
          margins =c(10,8),
          col=redblue(256),
          dendrogram="both",
          cexRow = 0.7,
          cexCol = 0.7,
          key.title = "PIP",
          lhei = c(1,3),
          lwid = c(0.5, 0.5),
          #Colv="NA"
          ) 

6.1 Variation in host condition

bas.model <- bas.lm(avcondition ~  T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + 
                      pool_riffle + meander + netcen + updist, 
                    data=environment2, prior="JZS")
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y) model 1    model 2    model 3    model 4    model 5
## Intercept       1.00000000  1.0000  1.0000000  1.0000000  1.0000000  1.0000000
## T_av            0.12386945  0.0000  1.0000000  0.0000000  0.0000000  0.0000000
## O2_sat_av       0.05073157  0.0000  0.0000000  0.0000000  0.0000000  0.0000000
## Con_av          0.03919858  0.0000  0.0000000  0.0000000  0.0000000  0.0000000
## COD_av          0.05197281  0.0000  0.0000000  0.0000000  0.0000000  1.0000000
## NH4._av         0.04846220  0.0000  0.0000000  0.0000000  0.0000000  0.0000000
## Nt_av           0.05248386  0.0000  0.0000000  0.0000000  0.0000000  0.0000000
## pool_riffle1    0.06729856  0.0000  0.0000000  0.0000000  1.0000000  0.0000000
## meander1        0.06527705  0.0000  0.0000000  0.0000000  0.0000000  0.0000000
## netcen          0.06898689  0.0000  0.0000000  1.0000000  0.0000000  0.0000000
## updist          0.04496936  0.0000  0.0000000  0.0000000  0.0000000  0.0000000
## BF                      NA  1.0000  0.6511099  0.3462387  0.2957714  0.2212089
## PostProbs               NA  0.6912  0.0450000  0.0239000  0.0204000  0.0153000
## R2                      NA  0.0000  0.0906000  0.0565000  0.0478000  0.0315000
## dim                     NA  1.0000  2.0000000  2.0000000  2.0000000  2.0000000
## logmarg                 NA  0.0000 -0.4290769 -1.0606268 -1.2181684 -1.5086476
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
#abs(coef.model$postmean)-2*coef.model$postsd > 0
plot(confint(coef.model, parm = 2:11))
## Warning in arrows(x[not.deg], ci[not.deg, 1], x[not.deg], ci[not.deg, 2], :
## zero-length arrow is of indeterminate angle and so skipped

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'condition.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(3:12),1] <- pip[2:11,1]*sign(coef.model$postmean[2:11])
#coef.model$postmean[2:11]

6.2 Variation in host length

bas.model <- bas.lm(avlength ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + 
                      pool_riffle + meander + netcen + updist, 
                    data=environment2, prior="JZS")
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)   model 1    model 2   model 3  model 4   model 5
## Intercept        1.0000000 1.0000000 1.00000000 1.0000000 1.000000 1.0000000
## T_av             0.1914598 0.0000000 0.00000000 0.0000000 0.000000 0.0000000
## O2_sat_av        0.1407247 0.0000000 0.00000000 0.0000000 0.000000 0.0000000
## Con_av           0.4373524 0.0000000 0.00000000 1.0000000 1.000000 0.0000000
## COD_av           0.1445232 0.0000000 0.00000000 0.0000000 0.000000 0.0000000
## NH4._av          0.2026061 0.0000000 0.00000000 0.0000000 0.000000 0.0000000
## Nt_av            0.1889236 0.0000000 0.00000000 0.0000000 0.000000 0.0000000
## pool_riffle1     0.2259504 0.0000000 0.00000000 0.0000000 0.000000 1.0000000
## meander1         0.3217534 0.0000000 0.00000000 0.0000000 1.000000 0.0000000
## netcen           0.6121912 1.0000000 0.00000000 0.0000000 0.000000 1.0000000
## updist           0.1480063 0.0000000 0.00000000 0.0000000 0.000000 0.0000000
## BF                      NA 0.8278694 0.07277547 0.2894406 1.000000 0.6785609
## PostProbs               NA 0.1582000 0.13910000 0.0553000 0.042500 0.0288000
## R2                      NA 0.2306000 0.00000000 0.1819000 0.314300 0.2982000
## dim                     NA 2.0000000 1.00000000 2.0000000 3.000000 3.0000000
## logmarg                 NA 2.4314765 0.00000000 1.3805712 2.620376 2.2325953
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
#abs(coef.model$postmean)-2*coef.model$postsd > 0
plot(confint(coef.model, parm = 2:11))
## Warning in arrows(x[not.deg], ci[not.deg, 1], x[not.deg], ci[not.deg, 2], :
## zero-length arrow is of indeterminate angle and so skipped

## Warning in arrows(x[not.deg], ci[not.deg, 1], x[not.deg], ci[not.deg, 2], :
## zero-length arrow is of indeterminate angle and so skipped

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'length.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(3:12),1] <- pip[2:11,1]*sign(coef.model$postmean[2:11])
#coef.model$postmean[2:11]

# Prediction plot
newdata = as.data.frame(cbind(rep(mean(environment2$T_av), 37), 
                rep(mean(environment2$O2_sat_av), 37),
                rep(mean(environment2$Con_av), 37),
                rep(mean(environment2$COD_av), 37),
                rep(mean(environment2$NH4._av), 37),
                rep(mean(environment2$Nt_av), 37),
                rep(1, 37),
                rep(1, 37),
                rep(mean(netcen), 37),
                rep(mean(updist), 37)))
colnames(newdata) <- c("T_av", "O2_sat_av", "Con_av", "COD_av", "NH4._av", "Nt_av", "pool_riffle", "meander", "netcen", "updist")
newdata[,"pool_riffle"] <- as.factor(newdata[,"pool_riffle"]); newdata[,"meander"] <- as.factor(newdata[,"meander"])
newdata1 <- newdata; newdata1[,"netcen"] <- netcen
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)

png(file="figure.png", res=600, width=3000, height=3000)

library(ggplot2)

figure_avlength <- ggplot(environment2, aes(netcen, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=netcen, y=avlength)) +
  labs(x=expression("Network peripherality [m]"), y=expression("Average host length [mm]")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
dev.off()
## png 
##   2
figure_avlength

6.3 Variation in Gyrodactylus infection

6.3.1 Mean abundance

bas.model <- bas.lm(avab$Gyr ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)  model 1    model 2   model 3   model 4   model 5
## Intercept        1.0000000 1.000000 1.00000000 1.0000000 1.0000000 1.0000000
## avlength         0.5500651 1.000000 0.00000000 0.0000000 0.0000000 1.0000000
## avcondition      0.3049274 0.000000 0.00000000 0.0000000 0.0000000 1.0000000
## T_av             0.1620852 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## O2_sat_av        0.2017699 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## Con_av           0.2621665 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## COD_av           0.8086300 1.000000 0.00000000 1.0000000 1.0000000 1.0000000
## NH4._av          0.2417809 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## Nt_av            0.8618345 1.000000 1.00000000 1.0000000 1.0000000 1.0000000
## pool_riffle1     0.1760484 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## meander1         0.1775842 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## netcen           0.3006370 0.000000 0.00000000 1.0000000 0.0000000 0.0000000
## updist           0.1648814 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## BF                      NA 1.000000 0.03902505 0.5452757 0.1537678 0.8271829
## PostProbs               NA 0.072100 0.05160000 0.0393000 0.0369000 0.0265000
## R2                      NA 0.524000 0.28790000 0.5059000 0.4100000 0.5631000
## dim                     NA 4.000000 2.00000000 4.0000000 3.0000000 5.0000000
## logmarg                 NA 6.997337 3.75378552 6.3908733 5.1250253 6.8076077
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     9.665145e-02 2.035129e-01  1.489134e-01
## avlength     -2.510048e-02 3.292762e-05 -8.122675e-03
## avcondition  -1.018870e+00 1.285004e-03 -1.500326e-01
## T_av         -1.817945e-02 1.869386e-02 -1.493132e-04
## O2_sat_av    -1.357600e-03 5.206338e-03  3.794809e-04
## Con_av       -8.116626e-05 5.132180e-04  5.726233e-05
## COD_av        0.000000e+00 1.283859e-02  6.652983e-03
## NH4._av      -7.496342e-02 5.641334e-02 -1.888173e-04
## Nt_av         0.000000e+00 5.236430e-02  2.930918e-02
## pool_riffle1 -5.509604e-02 8.247650e-02  3.966550e-03
## meander1     -1.013261e-01 4.005564e-02 -4.806259e-03
## netcen       -4.520712e-07 1.020908e-05  1.332021e-06
## updist       -1.263626e-06 1.831485e-06  4.618571e-08
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'GyroAA.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.3.1.1 Prediction plot for marginal effect of host condition on average Gyrodactylus infection

# Prediction plot
newdata = as.data.frame(cbind(rep(mean(avlength), 37),
                rep(mean(avcondition), 37),
                rep(mean(environment2$T_av), 37), 
                rep(mean(environment2$O2_sat_av), 37),
                rep(mean(environment2$Con_av), 37),
                rep(mean(environment2$COD_av), 37),
                rep(mean(environment2$NH4._av), 37),
                rep(mean(environment2$Nt_av), 37),
                rep(1, 37),
                rep(1, 37),
                rep(mean(netcen), 37),
                rep(mean(updist), 37)))
colnames(newdata) <- c("avlength", "avcondition", "T_av", "O2_sat_av", "Con_av", "COD_av", "NH4._av", "Nt_av", "pool_riffle", "meander", "netcen", "updist")
newdata[,"pool_riffle"] <- as.factor(newdata[,"pool_riffle"]); newdata[,"meander"] <- as.factor(newdata[,"meander"])
newdata1 <- newdata; newdata1[,"avcondition"] <- avcondition
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(avcondition, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=avcondition, y=avab$Gyr)) +
  labs(x=expression("Average host condition"), y=expression("Average Gyrodactylus count")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

6.3.1.2 Prediction plot for marginal effect of COD on average Gyrodactylus infection

newdata1 <- newdata; newdata1[,"COD_av"] <- environment2$COD_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(COD_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=COD_av, y=avab$Gyr)) +
  labs(x=expression("COD"), y=expression("Average Gyrodactylus count")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

6.3.2.3 Prediction plot for marginal effect of total nitrogen on average Gyrodactylus infection

newdata1 <- newdata; newdata1[,"Nt_av"] <- environment2$Nt_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(Nt_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=Nt_av, y=avab$Gyr)) +
  labs(x=expression("Nt"), y=expression("Average Gyrodactylus count")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

6.3.2 Median infection intensity

bas.model <- bas.lm(medin$Gyr ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
library(car)
## Loading required package: carData
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y) model 1    model 2   model 3    model 4    model 5
## Intercept       1.00000000  1.0000  1.0000000  1.000000  1.0000000  1.0000000
## avlength        0.02065469  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## avcondition     0.04286905  0.0000  1.0000000  0.000000  0.0000000  0.0000000
## T_av            0.02991678  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## O2_sat_av       0.02400544  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## Con_av          0.02143314  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## COD_av          0.03655302  0.0000  0.0000000  0.000000  1.0000000  0.0000000
## NH4._av         0.03250611  0.0000  0.0000000  0.000000  0.0000000  1.0000000
## Nt_av           0.04088810  0.0000  0.0000000  1.000000  0.0000000  0.0000000
## pool_riffle1    0.02307275  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## meander1        0.02038443  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## netcen          0.02173649  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## updist          0.02738794  0.0000  0.0000000  0.000000  0.0000000  0.0000000
## BF                      NA  1.0000  0.3176354  0.302852  0.2488803  0.2411373
## PostProbs               NA  0.7775  0.0206000  0.019600  0.0161000  0.0156000
## R2                      NA  0.0000  0.0517000  0.049100  0.0381000  0.0363000
## dim                     NA  1.0000  2.0000000  2.000000  2.0000000  2.0000000
## logmarg                 NA  0.0000 -1.1468512 -1.194511 -1.3907833 -1.4223890
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                  2.5%    97.5%          beta
## Intercept    1.560904 3.240035  2.405405e+00
## avlength     0.000000 0.000000 -5.938396e-04
## avcondition  0.000000 0.000000 -2.939823e-01
## T_av         0.000000 0.000000 -7.368692e-03
## O2_sat_av    0.000000 0.000000 -4.581964e-04
## Con_av       0.000000 0.000000 -1.594570e-05
## COD_av       0.000000 0.000000  1.609035e-03
## NH4._av      0.000000 0.000000  1.027436e-02
## Nt_av        0.000000 0.000000  7.570653e-03
## pool_riffle1 0.000000 0.000000  1.051497e-02
## meander1     0.000000 0.000000  2.511911e-03
## netcen       0.000000 0.000000  3.990331e-07
## updist       0.000000 0.000000  4.560731e-07
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'GyroAA.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.3.2 Prevalence

bas.model <- bas.lm(prev$Gyr ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
library(car)
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)  model 1    model 2   model 3   model 4     model 5
## Intercept       1.00000000 1.000000 1.00000000 1.0000000 1.0000000  1.00000000
## avlength        0.16685753 0.000000 0.00000000 0.0000000 1.0000000  0.00000000
## avcondition     0.07728991 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## T_av            0.07242807 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## O2_sat_av       0.09667222 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## Con_av          0.58076129 1.000000 0.00000000 1.0000000 0.0000000  0.00000000
## COD_av          0.17268847 0.000000 0.00000000 1.0000000 0.0000000  0.00000000
## NH4._av         0.09134534 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## Nt_av           0.11056039 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## pool_riffle1    0.13922799 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## meander1        0.09905733 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## netcen          0.11864979 0.000000 0.00000000 0.0000000 0.0000000  1.00000000
## updist          0.06837623 0.000000 0.00000000 0.0000000 0.0000000  0.00000000
## BF                      NA 1.000000 0.08283414 0.8857497 0.1246735  0.07409002
## PostProbs               NA 0.228800 0.22750000 0.0369000 0.0285000  0.01700000
## R2                      NA 0.233300 0.00000000 0.3039000 0.1341000  0.10730000
## dim                     NA 2.000000 1.00000000 3.0000000 2.0000000  2.00000000
## logmarg                 NA 2.490915 0.00000000 2.3695941 0.4088580 -0.11155941
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     2.490570e-01 3.923215e-01  3.224082e-01
## avlength     -2.272114e-02 0.000000e+00 -2.431148e-03
## avcondition  -4.217010e-01 1.626800e-02 -1.986363e-02
## T_av         -1.743285e-02 1.850250e-03 -7.123130e-04
## O2_sat_av    -4.604791e-03 3.272811e-05 -2.662986e-04
## Con_av        0.000000e+00 8.017249e-04  3.112530e-04
## COD_av        0.000000e+00 8.298397e-03  9.376253e-04
## NH4._av      -3.741585e-04 4.694160e-02  1.064409e-03
## Nt_av        -1.246419e-04 2.499388e-02  1.612509e-03
## pool_riffle1  0.000000e+00 1.537665e-01  1.465705e-02
## meander1     -1.130552e-01 3.190549e-04 -6.966751e-03
## netcen        0.000000e+00 8.426670e-06  5.765326e-07
## updist       -1.059535e-06 1.015335e-07 -6.922933e-09
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'GyroAA.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.3.2.3 Prediction plot for marginal effect of conductivity on average Gyrodactylus infection

newdata1 <- newdata; newdata1[,"Con_av"] <- environment2$Con_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(Con_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=Con_av, y=prev$Gyr)) +
  labs(x=expression("Conductivity"), y=expression("Gyrodactylus prevalence")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

6.4 Variation in Trichodina infection

6.4.1 Mean abundance

bas.model <- bas.lm(avab$Tri ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)   model 1  model 2  model 3   model 4   model 5
## Intercept       1.00000000 1.0000000 1.000000 1.000000 1.0000000 1.0000000
## avlength        0.12444042 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## avcondition     0.09559152 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## T_av            0.08500185 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## O2_sat_av       0.09751169 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## Con_av          0.42180029 0.0000000 1.000000 0.000000 0.0000000 0.0000000
## COD_av          0.46724539 0.0000000 1.000000 0.000000 0.0000000 1.0000000
## NH4._av         0.21465122 0.0000000 0.000000 0.000000 1.0000000 0.0000000
## Nt_av           0.34576751 0.0000000 0.000000 1.000000 0.0000000 1.0000000
## pool_riffle1    0.13743699 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## meander1        0.08968689 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## netcen          0.10313787 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## updist          0.08604777 0.0000000 0.000000 0.000000 0.0000000 0.0000000
## BF                      NA 0.0239404 1.000000 0.170643 0.1105942 0.2711811
## PostProbs               NA 0.1650000 0.104400 0.098000 0.0635000 0.0283000
## R2                      NA 0.0000000 0.358500 0.209300 0.1890000 0.3063000
## dim                     NA 1.0000000 3.000000 2.000000 2.0000000 3.0000000
## logmarg                 NA 0.0000000 3.732188 1.964006 1.5303004 2.4272192
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     1.229058e-01 2.721520e-01  2.002413e-01
## avlength     -1.582818e-02 1.162016e-03 -1.114390e-03
## avcondition  -4.894906e-01 1.211993e-01 -2.394139e-02
## T_av         -1.296026e-02 1.183449e-02 -1.479738e-04
## O2_sat_av    -1.315738e-03 4.296851e-03  1.132458e-04
## Con_av       -1.743950e-08 7.711874e-04  2.109076e-04
## COD_av       -1.858816e-06 1.395582e-02  4.203136e-03
## NH4._av      -2.507796e-05 1.100733e-01  1.096330e-02
## Nt_av        -2.448514e-05 4.941906e-02  1.044647e-02
## pool_riffle1  0.000000e+00 1.490229e-01  1.212839e-02
## meander1     -7.177485e-02 2.598627e-02 -1.678368e-03
## netcen       -6.140315e-06 1.237054e-06 -2.846749e-07
## updist       -1.003797e-06 9.794545e-07 -1.915234e-08
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'GyroAA.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.4.1 Median infection intensity

bas.model <- bas.lm(medin$Tri ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)  model 1    model 2   model 3   model 4   model 5
## Intercept        1.0000000 1.000000 1.00000000 1.0000000 1.0000000 1.0000000
## avlength         0.2881774 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## avcondition      0.2224163 0.000000 0.00000000 0.0000000 1.0000000 0.0000000
## T_av             0.1574615 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## O2_sat_av        0.1621652 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## Con_av           0.7912882 1.000000 0.00000000 1.0000000 1.0000000 1.0000000
## COD_av           0.7219333 1.000000 0.00000000 0.0000000 1.0000000 1.0000000
## NH4._av          0.3248706 0.000000 1.00000000 1.0000000 0.0000000 0.0000000
## Nt_av            0.3218716 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## pool_riffle1     0.2081402 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## meander1         0.2655250 0.000000 0.00000000 0.0000000 0.0000000 1.0000000
## netcen           0.2107764 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## updist           0.1536937 0.000000 0.00000000 0.0000000 0.0000000 0.0000000
## BF                      NA 1.000000 0.04957628 0.2279222 0.5092549 0.4837322
## PostProbs               NA 0.148800 0.04060000 0.0339000 0.0227000 0.0216000
## R2                      NA 0.449900 0.26810000 0.3987000 0.4816000 0.4799000
## dim                     NA 3.000000 2.00000000 3.0000000 4.0000000 4.0000000
## logmarg                 NA 6.288599 3.28435583 4.8098478 5.6137920 5.5623749
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     1.695452e+01 3.438593e+01  2.547297e+01
## avlength     -3.380690e+00 2.731409e-01 -5.158998e-01
## avcondition  -1.324481e+02 1.400968e+01 -1.375058e+01
## T_av         -2.029153e+00 4.134904e+00  2.065105e-01
## O2_sat_av    -5.947346e-01 4.319307e-01 -1.498026e-02
## Con_av        0.000000e+00 1.283100e-01  6.585727e-02
## COD_av        0.000000e+00 1.995554e+00  9.195418e-01
## NH4._av      -2.244992e+00 1.596905e+01  2.222211e+00
## Nt_av        -7.694817e-02 6.286264e+00  1.012166e+00
## pool_riffle1 -2.263931e+00 2.328611e+01  2.247962e+00
## meander1     -2.711917e+01 2.602300e-01 -3.523477e+00
## netcen       -1.375132e-03 2.494413e-04 -1.366046e-04
## updist       -2.245534e-04 2.760688e-04  5.653370e-06
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'GyroAA.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.3.2.3 Prediction plot for marginal effect of conductivity on median infection intensity with Trichodina

newdata1 <- newdata; newdata1[,"Con_av"] <- environment2$Con_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(Con_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=Con_av, y=medin$Tri)) +
  labs(x=expression("Conductivity"), y=expression("Trichodina median infection intensity")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

6.3.2.3 Prediction plot for marginal effect of COD on median infection intensity with Trichodina

newdata1 <- newdata; newdata1[,"COD_av"] <- environment2$COD_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(COD_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=COD_av, y=medin$Tri)) +
  labs(x=expression("Conductivity"), y=expression("Trichodina median infection intensity")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

6.4.1 Prevalence

bas.model <- bas.lm(prev$Tri ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)   model 1   model 2    model 3   model 4   model 5
## Intercept       1.00000000 1.0000000 1.0000000  1.0000000 1.0000000  1.000000
## avlength        0.04005815 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## avcondition     0.03389439 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## T_av            0.03654853 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## O2_sat_av       0.03749123 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## Con_av          0.20573471 0.0000000 1.0000000  0.0000000 1.0000000  0.000000
## COD_av          0.04629842 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## NH4._av         0.06690739 0.0000000 0.0000000  1.0000000 0.0000000  0.000000
## Nt_av           0.04604656 0.0000000 0.0000000  0.0000000 0.0000000  1.000000
## pool_riffle1    0.03411173 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## meander1        0.03657952 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## netcen          0.07467299 0.0000000 0.0000000  0.0000000 1.0000000  0.000000
## updist          0.07352673 0.0000000 0.0000000  0.0000000 0.0000000  0.000000
## BF                      NA 0.5616705 0.7274201  0.2732671 1.0000000  0.155205
## PostProbs               NA 0.6354000 0.0686000  0.0258000 0.0171000  0.014600
## R2                      NA 0.0000000 0.1264000  0.0750000 0.2249000  0.044000
## dim                     NA 1.0000000 2.0000000  2.0000000 3.0000000  2.000000
## logmarg                 NA 0.0000000 0.2585887 -0.7204656 0.5768398 -1.286169
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     7.801829e-01 8.849431e-01  8.340580e-01
## avlength      0.000000e+00 0.000000e+00 -1.453558e-04
## avcondition   0.000000e+00 0.000000e+00 -2.610917e-03
## T_av          0.000000e+00 0.000000e+00 -1.135202e-05
## O2_sat_av     0.000000e+00 0.000000e+00 -1.893466e-05
## Con_av        0.000000e+00 4.241640e-04  6.570599e-05
## COD_av        0.000000e+00 0.000000e+00  9.451636e-05
## NH4._av       0.000000e+00 1.819425e-02  1.713706e-03
## Nt_av         0.000000e+00 0.000000e+00  1.739937e-04
## pool_riffle1  0.000000e+00 0.000000e+00  2.104077e-04
## meander1      0.000000e+00 0.000000e+00 -6.652944e-04
## netcen       -3.849846e-06 3.938057e-08 -3.317353e-07
## updist       -1.358072e-06 0.000000e+00 -1.309710e-07
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
write.table(confint, 'GyroAA.txt', sep="\t")
pip <- summary(bas.model)
PIP[c(1:12),3] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.5 Variation in Glugea infection

bas.model <- bas.glm(pa$Glu ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av + 
                       NH4._av + Nt_av + SM_av + pool_riffle + meander + 
                       spavar$netcen + spavar$updist, data=environment2, betaprior=g.prior(100), family=binomial)
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##               P(B != 0 | Y)   model 1   model 2    model 3    model 4
## Intercept         1.0000000  1.000000  1.000000  1.0000000  1.0000000
## avlength          0.6612793  0.000000  0.000000  1.0000000  0.0000000
## avcondition       0.4488281  0.000000  1.000000  1.0000000  1.0000000
## T_av              0.2731201  0.000000  0.000000  0.0000000  0.0000000
## O2_sat_av         0.3873901  0.000000  0.000000  0.0000000  0.0000000
## Con_av            0.9977539  1.000000  1.000000  1.0000000  1.0000000
## COD_av            0.5381714  1.000000  0.000000  1.0000000  1.0000000
## NH4._av           0.8386841  1.000000  1.000000  1.0000000  1.0000000
## Nt_av             0.5621582  1.000000  1.000000  0.0000000  1.0000000
## SM_av             0.4463501  1.000000  1.000000  0.0000000  0.0000000
## pool_riffle1      0.4196533  0.000000  0.000000  0.0000000  0.0000000
## meander1          0.9978149  1.000000  1.000000  1.0000000  1.0000000
## spavar$netcen     0.4684082  0.000000  1.000000  0.0000000  0.0000000
## spavar$updist     0.8170898  1.000000  0.000000  1.0000000  1.0000000
## BF                       NA  1.000000  0.769804  0.8189871  0.7351301
## PostProbs                NA  0.048200  0.047300  0.0455000  0.0346000
## R2                       NA  1.000000  1.000000  1.0000000  1.0000000
## dim                      NA  8.000000  8.000000  8.0000000  8.0000000
## logmarg                  NA -5.808403 -6.070023 -6.0080902 -6.1161110
##                  model 5
## Intercept      1.0000000
## avlength       1.0000000
## avcondition    0.0000000
## T_av           0.0000000
## O2_sat_av      1.0000000
## Con_av         1.0000000
## COD_av         0.0000000
## NH4._av        0.0000000
## Nt_av          0.0000000
## SM_av          0.0000000
## pool_riffle1   1.0000000
## meander1       1.0000000
## spavar$netcen  1.0000000
## spavar$updist  1.0000000
## BF             0.5830791
## PostProbs      0.0299000
## R2             1.0000000
## dim            8.0000000
## logmarg       -6.3478357
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 569 > 1'
## in coercion to 'logical(1)'

## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 569 > 1'
## in coercion to 'logical(1)'
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE
confint(coef.model)
##                        2.5%        97.5%          beta
## Intercept     -2.825792e+06 2.710683e+06 -6.369350e+03
## avlength      -4.309607e+04 3.935300e+04  9.028577e+01
## avcondition   -9.449562e+05 9.095393e+05 -7.711752e+00
## T_av          -2.742780e+04 3.022164e+04  1.728316e+01
## O2_sat_av     -5.333463e+03 5.629149e+03  8.996676e+00
## Con_av        -1.563938e+03 1.596557e+03  4.398577e+00
## COD_av        -1.383043e+04 1.491038e+04  9.484729e+00
## NH4._av       -2.206263e+05 2.216950e+05 -2.719259e+02
## Nt_av         -4.701129e+04 4.562539e+04  3.847862e+01
## SM_av         -2.409398e+03 2.246281e+03 -1.183195e+00
## pool_riffle1  -1.415306e+05 1.540517e+05  8.128272e+01
## meander1      -5.313945e+05 4.746843e+05 -1.369205e+03
## spavar$netcen -1.073751e+01 9.266554e+00 -8.796714e-03
## spavar$updist -5.000750e+00 4.887079e+00 -8.188871e-03
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
pip <- summary(bas.model)
PIP[c(1:12),9] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

6.5 Variation in Contracaecum infection

bas.model <- bas.glm(pa$Con ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av + 
                       NH4._av + Nt_av + SM_av + pool_riffle + meander + 
                       spavar$netcen + spavar$updist, data=environment2, betaprior=g.prior(100), family=binomial)
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##               P(B != 0 | Y)   model 1     model 2     model 3     model 4
## Intercept        1.00000000   1.00000   1.0000000   1.0000000   1.0000000
## avlength         0.07762451   0.00000   1.0000000   0.0000000   0.0000000
## avcondition      0.02630615   0.00000   0.0000000   1.0000000   0.0000000
## T_av             0.01102295   0.00000   0.0000000   0.0000000   0.0000000
## O2_sat_av        0.02724609   0.00000   0.0000000   0.0000000   1.0000000
## Con_av           0.01230469   0.00000   0.0000000   0.0000000   0.0000000
## COD_av           0.01250000   0.00000   0.0000000   0.0000000   0.0000000
## NH4._av          0.01958008   0.00000   0.0000000   0.0000000   0.0000000
## Nt_av            0.01236572   0.00000   0.0000000   0.0000000   0.0000000
## SM_av            0.01303711   0.00000   0.0000000   0.0000000   0.0000000
## pool_riffle1     0.01182861   0.00000   0.0000000   0.0000000   0.0000000
## meander1         0.01090088   0.00000   0.0000000   0.0000000   0.0000000
## spavar$netcen    0.01875000   0.00000   0.0000000   0.0000000   0.0000000
## spavar$updist    0.01165771   0.00000   0.0000000   0.0000000   0.0000000
## BF                       NA   1.00000   0.9507459   0.2581488   0.2583995
## PostProbs                NA   0.79370   0.0548000   0.0152000   0.0150000
## R2                       NA   0.00000   0.0864000   0.0365000   0.0366000
## dim                      NA   1.00000   2.0000000   2.0000000   2.0000000
## logmarg                  NA -25.82594 -25.8764468 -27.1801577 -27.1791867
##                 model 5
## Intercept       1.00000
## avlength        0.00000
## avcondition     0.00000
## T_av            0.00000
## O2_sat_av       0.00000
## Con_av          0.00000
## COD_av          0.00000
## NH4._av         1.00000
## Nt_av           0.00000
## SM_av           0.00000
## pool_riffle1    0.00000
## meander1        0.00000
## spavar$netcen   0.00000
## spavar$updist   0.00000
## BF              0.19791
## PostProbs       0.01260
## R2              0.02640
## dim             2.00000
## logmarg       -27.44588
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 354 > 1'
## in coercion to 'logical(1)'

## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 354 > 1'
## in coercion to 'logical(1)'
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE
confint(coef.model)
##                    2.5%     97.5%          beta
## Intercept     -8.822922 2.2340459 -5.200393e-01
## avlength       0.000000 0.1521401  1.443680e-02
## avcondition    0.000000 0.0000000 -1.725841e-01
## T_av           0.000000 0.0000000  8.731866e-04
## O2_sat_av      0.000000 0.0000000  1.187055e-03
## Con_av         0.000000 0.0000000  7.077447e-06
## COD_av         0.000000 0.0000000 -3.261292e-04
## NH4._av        0.000000 0.0000000 -5.935914e-03
## Nt_av          0.000000 0.0000000 -9.420205e-04
## SM_av          0.000000 0.0000000  1.258097e-04
## pool_riffle1   0.000000 0.0000000 -5.262390e-03
## meander1       0.000000 0.0000000  3.109108e-03
## spavar$netcen  0.000000 0.0000000 -8.628183e-07
## spavar$updist  0.000000 0.0000000 -1.107421e-07
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
pip <- summary(bas.model)
PIP[c(1:12),10] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

Variation in Anguillicoloides infection

bas.model <- bas.glm(pa$Ang ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av + 
                       NH4._av + Nt_av + SM_av + pool_riffle + meander + 
                       spavar$netcen + spavar$updist, data=environment2, betaprior=g.prior(100), family=binomial)
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##               P(B != 0 | Y)   model 1     model 2     model 3     model 4
## Intercept         1.0000000  1.000000   1.0000000   1.0000000   1.0000000
## avlength          0.9590210  1.000000   1.0000000   1.0000000   1.0000000
## avcondition       0.3462524  0.000000   0.0000000   0.0000000   0.0000000
## T_av              0.9616455  1.000000   1.0000000   1.0000000   1.0000000
## O2_sat_av         0.8349487  1.000000   1.0000000   1.0000000   1.0000000
## Con_av            0.5795410  0.000000   1.0000000   1.0000000   0.0000000
## COD_av            0.3835938  0.000000   0.0000000   1.0000000   0.0000000
## NH4._av           0.9710571  1.000000   1.0000000   1.0000000   1.0000000
## Nt_av             0.5616821  0.000000   1.0000000   0.0000000   0.0000000
## SM_av             0.9464844  1.000000   1.0000000   1.0000000   1.0000000
## pool_riffle1      0.3850952  0.000000   0.0000000   0.0000000   1.0000000
## meander1          0.9624023  1.000000   1.0000000   1.0000000   1.0000000
## spavar$netcen     0.8757202  1.000000   1.0000000   1.0000000   1.0000000
## spavar$updist     0.5311157  1.000000   0.0000000   0.0000000   1.0000000
## BF                       NA  1.000000   0.4728289   0.3794633   0.2858158
## PostProbs                NA  0.075900   0.0701000   0.0502000   0.0420000
## R2                       NA  1.000000   1.0000000   1.0000000   1.0000000
## dim                      NA  9.000000  10.0000000  10.0000000  10.0000000
## logmarg                  NA -9.802499 -10.5515211 -10.7714968 -11.0549070
##                   model 5
## Intercept       1.0000000
## avlength        1.0000000
## avcondition     1.0000000
## T_av            1.0000000
## O2_sat_av       0.0000000
## Con_av          1.0000000
## COD_av          0.0000000
## NH4._av         1.0000000
## Nt_av           1.0000000
## SM_av           1.0000000
## pool_riffle1    0.0000000
## meander1        1.0000000
## spavar$netcen   1.0000000
## spavar$updist   0.0000000
## BF              0.2037316
## PostProbs       0.0320000
## R2              1.0000000
## dim            10.0000000
## logmarg       -11.3934513
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 330 > 1'
## in coercion to 'logical(1)'

## Warning in object$prior == "AIC" || object$prior == "BIC": 'length(x) = 330 > 1'
## in coercion to 'logical(1)'
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE
confint(coef.model)
##                        2.5%        97.5%          beta
## Intercept     -2.386597e+06 2.273643e+06 -6.535648e+03
## avlength      -4.586713e+04 4.408703e+04  1.346662e+02
## avcondition   -7.819640e+05 8.464993e+05 -3.655426e+02
## T_av          -1.630930e+05 1.565266e+05  6.012930e+02
## O2_sat_av     -1.997370e+04 1.776730e+04 -3.845302e+01
## Con_av        -6.764710e+02 6.776503e+02  3.950266e-01
## COD_av        -7.640585e+03 7.575599e+03  1.799636e+00
## NH4._av       -3.616578e+05 3.231969e+05 -1.075229e+03
## Nt_av         -4.446612e+04 4.557655e+04 -4.776944e+01
## SM_av         -5.506008e+03 6.217337e+03  1.312965e+01
## pool_riffle1  -1.379536e+05 1.324286e+05 -1.304974e+02
## meander1      -3.986089e+05 4.061205e+05 -1.417065e+03
## spavar$netcen -1.409875e+01 1.503926e+01 -2.813438e-02
## spavar$updist -3.898065e+00 2.878999e+00  1.216461e-03
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
pip <- summary(bas.model)
PIP[c(1:12),11] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

Variation in Individual Parasitation Index (all parasites)

bas.model <- bas.lm(avPI ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)    model 1    model 2    model 3  model 4  model 5
## Intercept        1.0000000 1.00000000 1.00000000 1.00000000 1.000000 1.000000
## avlength         0.2261960 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## avcondition      0.1810890 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## T_av             0.4574073 0.00000000 1.00000000 0.00000000 1.000000 0.000000
## O2_sat_av        0.1952767 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## Con_av           0.4598919 0.00000000 0.00000000 0.00000000 0.000000 1.000000
## COD_av           0.5684747 0.00000000 0.00000000 0.00000000 0.000000 1.000000
## NH4._av          0.2748144 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## Nt_av            0.4582802 0.00000000 0.00000000 1.00000000 1.000000 0.000000
## pool_riffle1     0.3054914 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## meander1         0.1985617 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## netcen           0.1910872 0.00000000 0.00000000 0.00000000 0.000000 0.000000
## updist           0.4153657 0.00000000 0.00000000 0.00000000 0.000000 1.000000
## BF                      NA 0.01969453 0.09251289 0.08737546 0.355023 1.000000
## PostProbs               NA 0.10850000 0.04250000 0.04010000 0.029600 0.025000
## R2                      NA 0.00000000 0.18980000 0.18710000 0.325400 0.424800
## dim                     NA 1.00000000 2.00000000 2.00000000 3.000000 4.000000
## logmarg                 NA 0.00000000 1.54700725 1.48987379 2.891842 3.927415
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     1.118420e+00 1.711581e+00  1.422090e+00
## avlength     -8.794753e-02 1.762219e-02 -7.992245e-03
## avcondition  -3.185059e+00 1.403626e+00 -9.325811e-02
## T_av         -3.274153e-03 3.715347e-01  8.644408e-02
## O2_sat_av    -2.698197e-02 1.308221e-02 -7.476618e-04
## Con_av       -5.439853e-06 3.163554e-03  8.405554e-04
## COD_av        0.000000e+00 6.150099e-02  2.109188e-02
## NH4._av      -5.045011e-01 1.915575e-01 -4.965441e-02
## Nt_av         0.000000e+00 2.286946e-01  5.507750e-02
## pool_riffle1 -5.094306e-02 8.726103e-01  1.389140e-01
## meander1     -6.379291e-01 2.037381e-01 -3.866036e-02
## netcen       -2.803839e-05 2.205411e-05 -1.270941e-06
## updist       -2.679058e-05 5.689670e-09 -5.952452e-06
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
pip <- summary(bas.model)
PIP[c(1:12),12] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

Prediction plot for marginal effect of COD on Individual Parasitation Index

newdata1 <- newdata; newdata1[,"COD_av"] <- environment2$COD_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(COD_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=COD_av, y=avPI)) +
  labs(x=expression("COD"), y=expression("Individual Parasitation Index")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

Variation in Individual Parasitation Index (only ectoparasites)

bas.model <- bas.lm(avPI_ecto ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)   model 1      model 2   model 3  model 4  model 5
## Intercept        1.0000000 1.0000000  1.000000000 1.0000000 1.000000 1.000000
## avlength         0.4669536 0.0000000  1.000000000 0.0000000 0.000000 1.000000
## avcondition      0.3758074 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## T_av             0.2753561 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## O2_sat_av        0.2919614 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## Con_av           0.6617062 0.0000000  1.000000000 1.0000000 0.000000 0.000000
## COD_av           0.8437205 0.0000000  1.000000000 1.0000000 1.000000 1.000000
## NH4._av          0.4163705 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## Nt_av            0.8302866 1.0000000  1.000000000 0.0000000 1.000000 1.000000
## pool_riffle1     0.4025108 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## meander1         0.5031625 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## netcen           0.3010717 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## updist           0.3285744 0.0000000  1.000000000 0.0000000 0.000000 0.000000
## BF                      NA 0.1318791  0.008313608 0.4282678 0.319205 1.000000
## PostProbs               NA 0.0510000  0.038600000 0.0301000 0.022500 0.021100
## R2                      NA 0.3007000  0.682800000 0.4141000 0.403700 0.496600
## dim                     NA 2.0000000 13.000000000 3.0000000 3.000000 4.000000
## logmarg                 NA 4.0635523  1.299560343 5.2414154 4.947500 6.089422
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     6.758354e-01 1.145843e+00  9.199577e-01
## avlength     -1.074205e-01 7.195116e-03 -2.357999e-02
## avcondition  -4.448220e+00 5.860600e-01 -7.055549e-01
## T_av         -9.391074e-02 1.376909e-01  5.818763e-03
## O2_sat_av    -1.425971e-02 2.512049e-02  1.122707e-03
## Con_av        0.000000e+00 3.201604e-03  1.203349e-03
## COD_av        0.000000e+00 6.383947e-02  3.405818e-02
## NH4._av      -4.856138e-01 7.930413e-02 -8.034086e-02
## Nt_av         0.000000e+00 2.520153e-01  1.257830e-01
## pool_riffle1 -5.647613e-02 8.378715e-01  1.490513e-01
## meander1     -9.300167e-01 0.000000e+00 -2.358742e-01
## netcen       -3.333049e-05 1.969508e-05 -2.447510e-06
## updist       -1.557366e-05 3.486981e-06 -1.836166e-06
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))

## NULL
confint <- confint(coef.model, parm = 2:11)
pip <- summary(bas.model)
PIP[c(1:12),13] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

Prediction plot for marginal effect of COD on Individual Parasitation Index (only ectoparasites)

newdata1 <- newdata; newdata1[,"COD_av"] <- environment2$COD_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(COD_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=COD_av, y=avPI_ecto)) +
  labs(x=expression("COD"), y=expression("Individual Parasitation Index (only ectoparasites)")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

Prediction plot for marginal effect of total nitrogen on Individual Parasitation Index (only ectoparasites)

newdata1 <- newdata; newdata1[,"Nt_av"] <- environment2$Nt_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(Nt_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=Nt_av, y=avPI_ecto)) +
  labs(x=expression("Total nitrogen"), y=expression("Individual Parasitation Index (only ectoparasites)")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

Prediction plot for marginal effect of conductivity on Individual Parasitation Index (only ectoparasites)

newdata1 <- newdata; newdata1[,"Con_av"] <- environment2$Con_av
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(Con_av, BMA$fit)) +
  theme_bw() +
  geom_line(color="red", size=1) +
  geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=Con_av, y=avPI)) +
  labs(x=expression("Conductivity"), y=expression("Individual Parasitation Index (only ectoparasites)")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

Prediction plot for marginal effect of meanders on Individual Parasitation Index (only ectoparasites)

newdata1 <- newdata; newdata1[,"meander"] <- environment2$meander
BMA <- predict(bas.model, newdata = newdata1, estimator = "BMA", se.fit=TRUE)
ggplot(environment2, aes(meander, BMA$fit)) +
  theme_bw() +
  #geom_line(color="red", size=1) +
  #geom_ribbon(aes(ymin = (BMA$fit-BMA$se.bma.fit), ymax = (BMA$fit+BMA$se.bma.fit)), alpha = .1) +
  geom_point(data = environment2, aes(x=meander, y=avPI)) +
  geom_boxplot(aes(lower = (BMA$fit-BMA$se.bma.fit), middle = BMA$fit, upper = (BMA$fit+BMA$se.bma.fit))) +
  labs(x=expression("Meander"), y=expression("Individual Parasitation Index (only ectoparasites)")) +
  theme(axis.title.x = element_text(size=12),
        axis.title.y = element_text(size=12)) +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

Variation in Individual Parasitation Index (only endoparasites)

bas.model <- bas.lm(avPI_endo ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2, prior="JZS")
yhat = fitted(bas.model, estimator = "BMA") #these are the fitted values under BMA
r = bas.model$Y - yhat #these are the model residuals
plot(bas.model)

summary(bas.model)
##              P(B != 0 | Y)   model 1  model 2     model 3    model 4   model 5
## Intercept       1.00000000 1.0000000 1.000000  1.00000000  1.0000000 1.0000000
## avlength        0.06442140 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## avcondition     0.12246410 0.0000000 0.000000  1.00000000  0.0000000 0.0000000
## T_av            0.30397004 0.0000000 1.000000  0.00000000  0.0000000 1.0000000
## O2_sat_av       0.05178919 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## Con_av          0.05158494 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## COD_av          0.04593088 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## NH4._av         0.08528364 0.0000000 0.000000  0.00000000  0.0000000 1.0000000
## Nt_av           0.06477759 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## pool_riffle1    0.04504579 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## meander1        0.05899866 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## netcen          0.05414430 0.0000000 0.000000  0.00000000  0.0000000 0.0000000
## updist          0.10936917 0.0000000 0.000000  0.00000000  1.0000000 0.0000000
## BF                      NA 0.3484238 1.000000  0.33059983  0.2877395 0.6134470
## PostProbs               NA 0.4921000 0.117700  0.03890000  0.0339000 0.0131000
## R2                      NA 0.0000000 0.166100  0.11040000  0.1032000 0.2244000
## dim                     NA 1.0000000 2.000000  2.00000000  2.0000000 3.0000000
## logmarg                 NA 0.0000000 1.054336 -0.05251095 -0.1913639 0.5656742
image(bas.model, rotate=F)

coef.model <- coef(bas.model)
abs(coef.model$postmean)-2*coef.model$postsd > 0
##  [1]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE
confint(coef.model)
##                       2.5%        97.5%          beta
## Intercept     3.151330e-01 7.021383e-01  4.947994e-01
## avlength     -1.412832e-03 1.080428e-02  1.398963e-03
## avcondition  -1.620055e-03 2.632662e+00  2.446911e-01
## T_av          0.000000e+00 2.126705e-01  4.520999e-02
## O2_sat_av    -2.267240e-04 1.121255e-06 -2.446396e-04
## Con_av        0.000000e+00 0.000000e+00 -1.385311e-05
## COD_av        0.000000e+00 0.000000e+00 -1.072193e-04
## NH4._av      -1.100309e-01 0.000000e+00 -9.322620e-03
## Nt_av        -2.432447e-02 0.000000e+00 -2.149910e-03
## pool_riffle1  0.000000e+00 0.000000e+00  2.267863e-03
## meander1      0.000000e+00 8.897285e-02  1.005422e-02
## netcen       -2.237261e-06 1.741707e-07 -3.607730e-07
## updist       -8.617171e-06 0.000000e+00 -8.091451e-07
## attr(,"Probability")
## [1] 0.95
## attr(,"class")
## [1] "confint.bas"
plot(confint(coef.model, parm = 2:11))
## Warning in arrows(x[not.deg], ci[not.deg, 1], x[not.deg], ci[not.deg, 2], :
## zero-length arrow is of indeterminate angle and so skipped

## NULL
confint <- confint(coef.model, parm = 2:11)
pip <- summary(bas.model)
PIP[c(1:12),14] <- pip[2:13,1]*sign(coef.model$postmean[2:13])

7. BORAL analysis

Model-based analysis of multivariate abundance data using Bayesian Markov chain Monte Carlo methods for parameter estimation

7.1 BORAL analysis for average abundances of parasites

library(boral)
## Loading required package: coda
## This is boral version 2.0. If you recently updated boral, please check news(package = "boral") for the updates in the latest version.
data$Site <- as.factor(data$site)
levels(data$site) <- levels(as.factor(environment2$Site))
data_m <- merge(data, environment2, by = "Site")
data_all <- na.omit(data_m) 
names(data_all)
##  [1] "Site"                "site"                "fish"               
##  [4] "parspeciesrichness"  "div_shannon"         "div_simpson"        
##  [7] "temp"                "pH"                  "conductivity"       
## [10] "nitrogen"            "phosphorus"          "oxygen"             
## [13] "netcen.x"            "updist.x"            "updist2"            
## [16] "updist3"             "fishspeciesrichness" "weight"             
## [19] "weigh..g."           "length"              "SMI"                
## [22] "Sex"                 "Gyr"                 "Tri"                
## [25] "Glu"                 "ecto_screener"       "Con"                
## [28] "CysL"                "Pro"                 "Aca"                
## [31] "Cam"                 "Ang"                 "CysI"               
## [34] "endo_screener"       "PI"                  "PI_ecto"            
## [37] "PI_endo"             "T_av"                "O2_sat_av"          
## [40] "Con_av"              "COD_av"              "NH4._av"            
## [43] "Nt_av"               "SM_av"               "pool_riffle"        
## [46] "meander"             "updist.y"            "netcen.y"
avcondition <- aggregate(data$SMI, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]
avlength <- aggregate(data$length, by = list(data[,1]), function(x){mean(x, na.rm =T)})[,2]

y <- round(cbind(avab$Gyr, avab$Tri, avab$Glu, avab$Con, avab$Ang))
X <- cbind(avcondition,
           avlength,
           environment2$T_av,
           environment2$O2_sat_av,
           environment2$Con_av,
           environment2$COD_av, 
           environment2$NH4._av, 
           environment2$Nt_av, 
           environment2$netcen, 
           environment2$updist, 
           as.numeric(environment2$pool_riffle), 
           as.numeric(environment2$meander))
colnames(X) <- c("avcondition", "avlength", "T", "O2", "Con", "COD", "NH4", "Nt", "netcen", "updist", "pool_riffle", "meander")

example_mcmc_control <- list(n.burnin = 1000, n.iteration = 10000, n.thin = 1)
testpath <- file.path(tempdir(), "jagsboralmodel.txt")
paramod <- boral(y, X = X,
                      family = "negative.binomial",
                      mcmc.control = example_mcmc_control,
                      model.name = testpath,
                      lv.control = list(num.lv = 2, type = "independent"),
                      save.model = TRUE)
## module glm loaded
## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 185
##    Unobserved stochastic nodes: 338
##    Total graph size: 2173
## 
## Initializing model
plot(paramod)
## NULL

coefsplot(covname = "avcondition", object = paramod) #Condition

coefsplot(covname = "avlength", object = paramod) #Length

coefsplot(covname = "T", object = paramod) #Temperature

coefsplot(covname = "O2", object = paramod) #Oxygen

coefsplot(covname = "Con", object = paramod) #Conductivity

coefsplot(covname = "COD", object = paramod) #COD

coefsplot(covname = "NH4", object = paramod) #NH4

coefsplot(covname = "Nt", object = paramod) #Nt

coefsplot(covname = "netcen", object = paramod) #netcen

coefsplot(covname = "updist", object = paramod) #updist

coefsplot(covname = "pool_riffle", object = paramod) #poolriffle

coefsplot(covname = "meander", object = paramod) #meander

envcors <- get.enviro.cor(paramod)
rescors <- get.residual.cor(paramod)
library(corrplot)
## corrplot 0.92 loaded
corrplot(envcors$sig.cor, type = "lower", diag = FALSE, title = "Correlations due to covariates", mar = c(3,0.5,2,1), tl.srt = 45)

corrplot(rescors$sig.cor, type = "lower", diag = FALSE, title = "Residual correlations", mar = c(3,0.5,2,1), tl.srt = 45)

7.1 BORAL analysis for median infection intensities of parasites

y <- round(cbind(medin$Gyr, medin$Tri, medin$Glu, medin$Con, medin$Ang))
paramod <- boral(y, X = X,
                      family = "negative.binomial",
                      mcmc.control = example_mcmc_control,
                      model.name = testpath,
                      lv.control = list(num.lv = 2, type = "independent"),
                      save.model = TRUE)
## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 185
##    Unobserved stochastic nodes: 338
##    Total graph size: 2173
## 
## Initializing model
plot(paramod)
## NULL

coefsplot(covname = "avcondition", object = paramod) #Condition

coefsplot(covname = "avlength", object = paramod) #Length

coefsplot(covname = "T", object = paramod) #Temperature

coefsplot(covname = "O2", object = paramod) #Oxygen

coefsplot(covname = "Con", object = paramod) #Conductivity

coefsplot(covname = "COD", object = paramod) #COD

coefsplot(covname = "NH4", object = paramod) #NH4

coefsplot(covname = "Nt", object = paramod) #Nt

coefsplot(covname = "netcen", object = paramod) #netcen

coefsplot(covname = "updist", object = paramod) #updist

coefsplot(covname = "pool_riffle", object = paramod) #poolriffle

coefsplot(covname = "meander", object = paramod) #meander

envcors <- get.enviro.cor(paramod)
rescors <- get.residual.cor(paramod)
library(corrplot)
corrplot(envcors$sig.cor, type = "lower", diag = FALSE, title = "Correlations due to covariates", mar = c(3,0.5,2,1), tl.srt = 45)

corrplot(rescors$sig.cor, type = "lower", diag = FALSE, title = "Residual correlations", mar = c(3,0.5,2,1), tl.srt = 45)

8. Multivariate analysis

8.1 Component communities

# Component communities: Bray-Curtis dissimilarities based on Hellinger transformed average abundance data
spe.hel_bray <- vegdist(decostand(avab[,-1], na.rm=T, method="hellinger"), method="bray", na.rm=T)

# Check whether Euclidean and Bray-Curtis distances are comparable
spe.hel_euc <- vegdist(decostand(avab[,-1], na.rm=T, method="hellinger"), method="euc", na.rm=T)
plot(spe.hel_bray, spe.hel_euc)

mantel(spe.hel_bray, spe.hel_euc)
## 
## Mantel statistic based on Pearson's product-moment correlation 
## 
## Call:
## mantel(xdis = spe.hel_bray, ydis = spe.hel_euc) 
## 
## Mantel statistic r: 0.9648 
##       Significance: 0.001 
## 
## Upper quantiles of permutations (null model):
##   90%   95% 97.5%   99% 
## 0.110 0.146 0.177 0.198 
## Permutation: free
## Number of permutations: 999
adonis(spe.hel_bray ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2)
## 'adonis' will be deprecated: use 'adonis2' instead
## $aov.tab
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs MeanSqs F.Model      R2 Pr(>F)  
## avlength     1    0.1863 0.18629  1.8398 0.04303  0.118  
## avcondition  1    0.1305 0.13055  1.2893 0.03016  0.309  
## T_av         1    0.3204 0.32039  3.1643 0.07401  0.014 *
## O2_sat_av    1    0.1368 0.13678  1.3509 0.03160  0.259  
## Con_av       1    0.1326 0.13262  1.3098 0.03064  0.283  
## COD_av       1    0.0657 0.06568  0.6486 0.01517  0.641  
## NH4._av      1    0.2040 0.20399  2.0146 0.04712  0.098 .
## Nt_av        1    0.1451 0.14509  1.4329 0.03352  0.224  
## pool_riffle  1    0.0853 0.08529  0.8424 0.01970  0.544  
## meander      1    0.2029 0.20286  2.0035 0.04686  0.092 .
## netcen       1    0.2173 0.21728  2.1459 0.05019  0.074 .
## updist       1    0.0719 0.07193  0.7104 0.01662  0.597  
## Residuals   24    2.4301 0.10125         0.56137         
## Total       36    4.3288                 1.00000         
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $call
## adonis(formula = spe.hel_bray ~ avlength + avcondition + T_av + 
##     O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + 
##     meander + netcen + updist, data = environment2)
## 
## $coefficients
## NULL
## 
## $coef.sites
##                       [,1]          [,2]          [,3]          [,4]
## (Intercept)   5.508408e-01 -5.273740e-02 -2.434806e-01  9.195991e-02
## avlength     -6.730327e-03 -5.154478e-03 -3.437304e-03  3.017426e-03
## avcondition   3.533446e-01  6.299677e-01  6.705073e-01 -1.509499e-01
## T_av          1.118039e-02 -1.547332e-02  2.284308e-02  3.609975e-02
## O2_sat_av    -1.952659e-03  3.216838e-03 -2.736684e-03 -3.275301e-03
## Con_av       -5.105173e-04 -7.421868e-05 -2.766052e-04 -2.644205e-04
## COD_av       -2.877120e-03  2.012742e-03 -5.828066e-04  2.055569e-03
## NH4._av       2.840428e-02  2.361253e-02 -5.333225e-02 -1.083596e-01
## Nt_av        -1.398084e-02  3.352012e-03  1.765257e-02  1.505213e-02
## pool_riffle1  1.768819e-02 -5.367793e-04  3.673375e-03  2.606624e-02
## meander1     -7.321195e-02 -1.737680e-02  3.462634e-02 -6.906184e-03
## netcen        5.687407e-06  3.122369e-06  6.705984e-06  7.354323e-06
## updist       -7.990288e-07 -3.330355e-07  1.097578e-07 -1.418553e-06
##                       [,5]          [,6]          [,7]          [,8]
## (Intercept)   3.417559e-01  6.599748e-01 -6.656732e-01  1.232299e+00
## avlength     -5.220827e-03 -8.875861e-03  1.624719e-02 -8.270956e-03
## avcondition   7.063362e-01  5.898287e-01 -9.628888e-02  1.786671e-01
## T_av          3.555749e-03 -2.036964e-02  7.082503e-02 -1.630523e-02
## O2_sat_av    -3.559094e-03 -3.677428e-03 -1.366724e-03 -3.240107e-03
## Con_av       -2.630009e-04 -3.274615e-04  1.607746e-04 -2.325954e-04
## COD_av       -1.859208e-03 -1.344927e-03 -2.168911e-03 -1.552806e-03
## NH4._av      -1.230503e-02 -6.366620e-03 -2.906617e-02  3.139836e-02
## Nt_av         3.624518e-03  6.253769e-03 -2.142983e-02  2.965146e-04
## pool_riffle1 -1.857388e-02 -1.937103e-02  1.767055e-02 -2.156985e-02
## meander1      3.644385e-03 -3.037137e-02 -3.142557e-02 -1.319176e-02
## netcen        4.247947e-06  8.553556e-06 -2.836475e-06  2.289602e-06
## updist       -1.160792e-06 -1.516476e-06 -9.041883e-07 -5.879432e-07
##                       [,9]         [,10]         [,11]         [,12]
## (Intercept)   1.193606e-02 -6.431572e-01  1.029606e+00  9.925732e-02
## avlength      1.017386e-02  1.482368e-02 -5.945561e-03 -3.107184e-03
## avcondition   1.420036e-01 -7.065401e-02  1.459360e-01  2.553069e-01
## T_av          3.532679e-02  6.659019e-02 -1.879500e-02  4.397943e-03
## O2_sat_av    -1.109085e-03 -1.780974e-03  9.211405e-05  1.062527e-04
## Con_av        2.249288e-04  4.161917e-05 -2.084932e-04 -1.073458e-04
## COD_av       -2.925292e-03 -2.013086e-03 -1.816569e-03 -1.936453e-04
## NH4._av       1.700026e-03 -3.587351e-02  7.085431e-02 -3.570309e-04
## Nt_av        -2.464491e-02 -2.042881e-02 -2.756268e-02 -2.613938e-03
## pool_riffle1  5.149964e-03  2.434934e-02 -7.384338e-03 -1.940375e-02
## meander1     -3.592391e-02 -3.093900e-02 -1.011602e-01 -2.896967e-02
## netcen       -4.890078e-06  2.155102e-08  2.116885e-07  3.898399e-06
## updist       -2.556568e-06 -9.169728e-07 -4.186830e-07  9.989285e-07
##                      [,13]         [,14]         [,15]         [,16]
## (Intercept)  -6.368613e-01  7.803088e-01 -7.166398e-01  6.265197e-01
## avlength      1.681428e-02 -1.615996e-02  1.599244e-02 -4.870955e-04
## avcondition  -9.852280e-02  1.116504e+00 -8.864468e-02 -2.266528e-01
## T_av          6.899743e-02 -5.281902e-02  7.019720e-02 -2.675075e-02
## O2_sat_av    -1.154303e-03  8.408912e-04 -1.528332e-03  2.683281e-03
## Con_av        2.133819e-04 -1.628458e-04  1.210939e-04  9.193730e-05
## COD_av       -2.256399e-03 -3.417431e-04 -1.905709e-03  1.685274e-03
## NH4._av      -2.351319e-02  2.216998e-02 -3.305408e-02 -2.101423e-03
## Nt_av        -2.236658e-02  2.414900e-02 -2.133049e-02 -4.373715e-03
## pool_riffle1  1.777876e-02 -1.073611e-02  2.225968e-02 -1.085855e-02
## meander1     -3.052164e-02  2.795040e-02 -3.051222e-02 -2.956997e-02
## netcen       -3.753005e-06  2.977032e-06 -1.286598e-06  3.095126e-06
## updist       -1.122169e-06 -7.836708e-07 -8.604971e-07  2.315622e-07
##                      [,17]         [,18]         [,19]         [,20]
## (Intercept)  -6.121613e-01 -6.298597e-01  3.672728e-01 -4.193382e-01
## avlength      1.697894e-02  2.055352e-02 -7.171231e-04  1.005516e-02
## avcondition  -7.389408e-02 -6.777901e-02 -2.887636e-02 -5.762375e-02
## T_av          6.585840e-02  6.131461e-02  4.014584e-03  4.493748e-02
## O2_sat_av    -8.101716e-04  5.594262e-05  2.683683e-03 -8.807157e-04
## Con_av        2.549962e-04  3.822115e-04 -2.856617e-04  4.572917e-05
## COD_av       -2.152015e-03 -2.748748e-03 -1.553914e-03 -1.849240e-03
## NH4._av      -1.868318e-02  4.450495e-03  7.811332e-02 -4.979537e-03
## Nt_av        -2.305085e-02 -2.703083e-02 -1.925957e-02 -1.841033e-02
## pool_riffle1  1.402088e-02  5.461863e-03  4.427048e-02  1.431926e-02
## meander1     -2.516039e-02 -7.084940e-03 -9.584558e-02 -5.261891e-02
## netcen       -4.556663e-06 -6.879221e-06  1.369068e-06  8.289165e-07
## updist       -1.287669e-06 -1.451850e-06  1.280760e-06  6.116341e-09
##                      [,21]         [,22]         [,23]         [,24]
## (Intercept)  -6.532464e-01  4.100449e-02  1.704589e-01  6.462801e-01
## avlength      2.319031e-02 -7.043442e-03  3.719695e-03 -1.151131e-02
## avcondition  -1.226451e-01  4.981712e-01 -2.975572e-01  2.656163e-01
## T_av          6.921670e-02  9.203739e-03  3.604248e-02  3.693320e-03
## O2_sat_av    -5.363793e-04 -3.377174e-03 -2.104368e-03 -3.267513e-03
## Con_av        4.666038e-04 -4.483003e-04 -3.957322e-04 -7.538767e-04
## COD_av       -3.665123e-03  1.139311e-04 -1.331837e-03 -1.247580e-03
## NH4._av       1.098478e-02 -5.822747e-02  7.918302e-04 -5.527844e-03
## Nt_av        -2.846609e-02  2.913377e-02 -1.519403e-02  1.263706e-02
## pool_riffle1  5.976844e-03 -2.818818e-03  3.112259e-02  5.198239e-03
## meander1     -4.555456e-03  1.470428e-02 -8.750494e-02 -6.113122e-02
## netcen       -7.704644e-06  1.084062e-05  6.382930e-06  1.250120e-05
## updist       -1.047127e-06  5.517250e-07 -2.895584e-07  1.103984e-06
##                      [,25]         [,26]         [,27]         [,28]
## (Intercept)   6.769474e-01  6.020722e-03  7.029508e-01 -6.495116e-01
## avlength      6.564463e-03 -3.847984e-03 -5.761959e-03  4.172387e-03
## avcondition  -4.822334e-01  3.529973e-01 -1.612682e-01  5.898298e-01
## T_av          2.561781e-02  1.361892e-03 -4.982493e-03  4.612126e-02
## O2_sat_av     1.904383e-03  2.383360e-04  6.440399e-04 -1.955014e-03
## Con_av        2.945301e-04 -1.586756e-04 -5.006992e-04 -1.366137e-04
## COD_av        2.920903e-04 -8.000102e-05 -1.425778e-03 -2.044311e-03
## NH4._av       2.523120e-02 -4.970698e-03  3.710533e-02 -2.533041e-02
## Nt_av        -3.061194e-02  8.474961e-04 -4.119371e-03  3.362813e-03
## pool_riffle1  1.748158e-02 -1.825549e-02  2.758115e-02  1.081138e-02
## meander1     -5.239307e-03 -2.501497e-02 -9.167294e-02  1.744373e-02
## netcen       -8.945792e-06  5.603190e-06  8.449204e-06  1.762466e-06
## updist       -2.988354e-07  8.492801e-07  1.866830e-06  1.009091e-06
##                      [,29]         [,30]         [,31]         [,32]
## (Intercept)   1.664279e+00  6.279966e-01 -1.746030e-01  4.404427e-01
## avlength     -1.236214e-02 -7.011657e-03  7.012405e-03 -1.778983e-03
## avcondition   2.858156e-01  4.234981e-01 -2.258974e-01  1.622057e-01
## T_av         -5.986930e-02 -2.173927e-03  5.234007e-02  9.365206e-03
## O2_sat_av    -3.463527e-04 -1.347510e-03 -3.029788e-03 -2.410160e-03
## Con_av       -4.356963e-05 -3.400522e-04 -2.095022e-04 -3.845398e-04
## COD_av        1.130715e-03 -3.344424e-03  6.944179e-04 -2.171721e-03
## NH4._av       2.536027e-02  6.093858e-02 -7.590807e-02  5.297513e-03
## Nt_av        -5.922196e-03 -1.726172e-02  5.007697e-04 -9.117520e-03
## pool_riffle1 -5.179915e-02  4.786601e-03  3.134113e-02  2.786768e-02
## meander1     -4.388545e-02 -8.632094e-02 -2.294827e-02 -6.533310e-02
## netcen        1.380107e-06  2.562367e-06  5.466809e-06  6.786009e-06
## updist       -1.505678e-06  3.457645e-07 -1.297399e-06 -1.391436e-06
##                      [,33]         [,34]         [,35]         [,36]
## (Intercept)   3.101886e-01 -2.542264e-01 -2.501988e-01  8.628936e-01
## avlength     -3.162267e-03  7.673672e-03 -2.941552e-03 -9.795749e-03
## avcondition   4.018815e-02 -7.033370e-02  5.630407e-01  5.245065e-01
## T_av         -2.895238e-03  5.432776e-02  2.745586e-02 -2.040254e-02
## O2_sat_av     2.413948e-03  5.390887e-04 -3.582597e-03 -2.035098e-03
## Con_av       -3.367390e-04 -2.833619e-04 -3.887135e-04 -2.231771e-04
## COD_av       -6.546298e-04 -3.187515e-03  4.168535e-04 -1.534188e-03
## NH4._av       4.520826e-02  3.397592e-02 -8.031235e-02  2.546175e-02
## Nt_av        -1.636260e-02 -2.714229e-02  2.683761e-02  1.781403e-02
## pool_riffle1  6.586967e-04  3.365024e-02  4.205757e-03  6.631058e-03
## meander1     -8.882833e-02 -8.347203e-02  3.115884e-02  2.286827e-02
## netcen        5.008203e-06 -1.089956e-07  8.862842e-06  2.456590e-06
## updist        1.614076e-06  1.190913e-06  6.126184e-08  6.118538e-07
##                      [,37]
## (Intercept)  -1.060510e-01
## avlength      3.588634e-03
## avcondition   1.124134e-01
## T_av          4.012527e-02
## O2_sat_av    -2.040541e-03
## Con_av       -2.358599e-04
## COD_av       -2.983090e-03
## NH4._av       1.721446e-02
## Nt_av        -1.453435e-02
## pool_riffle1  1.079718e-02
## meander1     -6.948440e-02
## netcen        2.399692e-06
## updist        7.900733e-07
## 
## $f.perms
##                 [,1]        [,2]         [,3]         [,4]         [,5]
##    [1,]  2.722531523  5.21174869  0.727412423  1.801691080  1.413524954
##    [2,]  0.829082633  0.44866500  1.390122596  1.809911318  1.177274230
##    [3,]  0.243683653  1.34467885  0.407694203  0.498946229  0.441320261
##    [4,]  0.202895266  0.86657436  0.210269656  1.498158685  0.019049899
##    [5,]  0.889758373  1.28038123  0.718313557  1.256777635  1.485339072
##    [6,]  0.843675436  0.26075053  0.714965659  0.636728778  0.444388809
##    [7,]  1.347152180  1.04154613  0.345972527  0.911616683  0.687946657
##    [8,]  0.774031776  0.41380392  1.077717278  1.149371342  0.747734470
##    [9,]  0.768404665  1.84841264  0.733277679  1.156950176  0.581540715
##   [10,] -0.005148485  1.88780388  1.376966754  1.792548645  0.237932084
##   [11,]  0.540555425  0.34626680  0.651145346  0.343817464  1.367790785
##   [12,]  0.291213554  0.46940340  0.466770952  0.708663847  0.116579511
##   [13,]  1.470117844  1.52938217  1.371213015  0.628970697  0.301800525
##   [14,]  4.477660409  0.18770144  1.343814749  1.059070051  3.121673393
##   [15,]  2.103304619  1.22412350  0.806694108  0.929245092  0.598755742
##   [16,]  0.649426243  1.36991868  0.941887742  2.212728279  1.424006520
##   [17,]  2.027402531  1.47289122  0.812892561  0.719637746  1.123235167
##   [18,]  1.214519514  0.85014419  0.596021596  0.688675691  0.115034201
##   [19,]  0.109750985  0.45266650  0.414196814  2.256468581  0.440316378
##   [20,]  1.095447700  0.53423068  2.813417410  1.195597713  0.556442417
##   [21,]  2.052125974  0.20151313  2.331216143  1.171040446  1.461442067
##   [22,]  1.078779010  2.18972677  0.031270964  0.540947574  1.031891576
##   [23,]  2.021210315  0.59937133  0.950023802  3.683133058  2.283025109
##   [24,]  0.886531107  1.62972562  0.442661754  0.319314380  1.013481929
##   [25,]  1.574837192  0.35384294  0.208450477  0.961476035  1.601736307
##   [26,]  0.235575630  1.00156591  1.037274769  1.445365155  0.309517589
##   [27,]  0.654441240  1.56662483  0.693195166  0.407999106  1.562114187
##   [28,]  2.077517854  0.22755268  0.568833182  0.532306348  0.445977445
##   [29,]  1.522203708  1.85098964  0.663131167  0.833495854  2.043276389
##   [30,]  4.455577359  0.52106967  2.266031474  0.349586657  0.288509899
##   [31,]  2.242655182  0.26386874  0.580914240  0.797950509  2.794623041
##   [32,]  0.861448557  0.80211596  2.621799191  0.605966695  0.369615504
##   [33,]  0.445059027  0.42240232  1.796463812  1.790787534  0.731860578
##   [34,]  1.206812764  1.44521533  0.648879336  0.669895851  0.916318670
##   [35,]  0.197149117  0.51033946  0.240674153  0.295339966  0.334197361
##   [36,]  1.047318681  2.23481886  0.731540818  0.560897176  0.672113463
##   [37,]  1.134509452  0.14733442  0.368893094  0.339704623  0.579117708
##   [38,]  0.466871194  1.18439024  0.802191855  1.709256307  1.958827661
##   [39,]  0.665114221  0.96975950  0.181278131  1.655517743  0.099398363
##   [40,]  0.912251828  0.66618739  0.168072022  0.693359488  1.418249246
##   [41,]  0.859573775  0.52591309  1.122074342  0.751998875  0.280118512
##   [42,]  1.126940793  0.49107977  2.924304701  2.312873687  1.536573086
##   [43,]  0.952750565  0.37191252  0.424486044  0.234014586  1.397677121
##   [44,]  0.707865779  1.08067395  0.054073543  1.552541486  0.197563286
##   [45,]  0.927074814  1.13121300  0.615262623  1.280496266  0.058105860
##   [46,]  0.658674580  2.20816322  0.515208346  0.404637826  1.684557698
##   [47,]  3.138514168  0.92446147  1.069470329  1.248142851  0.396869363
##   [48,]  0.290252251  1.58494413  1.686009051  0.899239579  1.290249602
##   [49,]  0.766620776  0.32395349  1.353404603  1.102428347  0.198950807
##   [50,]  0.290365060  0.51002303  1.054681465  1.568629161  0.679049668
##   [51,]  4.283850085  0.76926014  2.171437826  1.995539644  0.274555327
##   [52,]  0.055658057  1.35186031  2.174618333  0.484059509  1.328534195
##   [53,]  2.257689302  0.59946016  0.519800881  0.198423303  0.891784679
##   [54,]  0.979773144  2.10749732  0.227509092  1.032150857  0.890674661
##   [55,]  0.490845836  0.50841356  0.657854930  0.490632550  1.276867772
##   [56,]  0.823847826  0.59067502  0.364837136  0.690482411  1.018004629
##   [57,]  0.481895277  2.05523106  2.904096879  0.749410675  0.719894111
##   [58,]  0.505558724  1.92317261  0.949861402  2.208680986  2.425643680
##   [59,]  2.309394413  3.33821222  1.037265168  0.909712416  0.768442174
##   [60,]  0.536797755  0.35563615  0.692785962  0.992873286  0.399913923
##   [61,]  0.632847680  1.02487972  1.027291643  1.010795500  0.804145115
##   [62,]  0.630848948  1.90152131  1.139116122  0.825668132  0.596401276
##   [63,]  0.456767473  0.40470616  0.409564847  1.351530148  1.795408367
##   [64,]  0.223792914  1.00451508  1.179725540  1.066890384  1.023009627
##   [65,]  1.399415855  0.03304097  0.690731857  0.813563153  3.208031028
##   [66,]  1.075878256  0.53496769  0.115463481  4.049132204  1.936826539
##   [67,]  0.690656422  0.46414290  1.637369398  1.237195387  0.862205941
##   [68,]  0.750287931  0.51919198  0.762365290  1.429638771  1.087952111
##   [69,]  0.867717647  0.21154364  1.105340889  1.681052361  1.412125942
##   [70,]  0.680764794  0.39796815  2.150882614  2.741180415  1.420567713
##   [71,]  1.199553369  0.79883361  1.228299233  1.361895561  0.733803072
##   [72,]  0.524296208  2.33892094  0.922729910  0.070782646  0.608990296
##   [73,]  1.184047651  0.70422746  1.096038878  0.149876950  0.683514589
##   [74,]  0.059122172  0.62104252  0.258628704  0.536362917  0.316668983
##   [75,]  0.262365967  1.09968108  0.227610036  0.622418504  1.260722514
##   [76,]  1.199357417  0.32842696  1.721521240  0.690972283  2.719816208
##   [77,]  0.463232084  1.08524821  0.186066018  0.329223112  1.047812421
##   [78,]  1.172297875  0.80259419  0.704259305  0.685377689  0.496038461
##   [79,]  0.869812347  4.00132206  0.990986758  0.388609349  1.514256604
##   [80,]  0.400233806  0.32134761 -0.007942901  0.389166229  0.543703692
##   [81,]  1.384535061  0.06498657  0.467612307  1.892070410  1.077695511
##   [82,]  1.121772304  1.34573236  1.208081696  0.775780430  1.384059051
##   [83,]  1.438857703  2.27985422  0.889052982 -0.134638559  0.660661177
##   [84,]  1.990823552  0.33575617  4.315281514  1.457388010  1.931879703
##   [85,]  1.087512837  0.24516847  1.030826042  0.999348592  0.373933720
##   [86,]  0.464191198  0.72515741  1.005569767  0.571566404  1.846769675
##   [87,]  0.802755418  0.43436844  2.741623162  0.773730055  1.321577324
##   [88,]  1.302741831  2.44623854  0.041217701  1.805745127  1.394509175
##   [89,]  0.545374890  1.22114916  0.161076366  0.522413100  0.290407332
##   [90,]  0.856464350  2.30123316  0.682273072  1.406964816  0.535804122
##   [91,]  0.640202093  0.47327648  2.362075617  0.370480470  1.129869746
##   [92,]  0.533878607  2.01281925  0.862810036  1.073172445  0.866201336
##   [93,]  0.271242559  1.46672981  0.404034041  5.309219816  1.634929075
##   [94,]  0.355354722  2.31680136  1.791464057 -0.029447287  0.198929785
##   [95,]  0.382873935  1.58161123  1.355133395  1.296242564  0.235217350
##   [96,]  1.212467978  0.37156934  0.089488940  0.211765523  0.582525225
##   [97,]  0.520270373  1.32199364  0.646674463  0.878475773  0.179479636
##   [98,]  1.390245445  0.94886127  0.139722835  0.416603234  0.711415818
##   [99,]  2.365395438  1.30489477  2.054398713  3.121116543  0.677921002
##  [100,]  1.224463737  0.68240776  0.333964664  1.623948964  1.265560534
##  [101,]  0.506659713  0.74051082  0.075654952  0.770128878  0.578450038
##  [102,]  1.818027123  0.33256109  0.380885136  0.831565589  1.388716191
##  [103,]  0.399565657  0.57117092  0.468473922  0.169971368  1.334749632
##  [104,]  1.423371325  0.29038230  0.837826388  0.236527647  1.043929921
##  [105,]  1.249791903  1.45288834  0.696040760  0.300394813  0.893155613
##  [106,]  1.755733715  0.66725312  1.047766014  0.421246360  2.167940066
##  [107,]  0.257424378  1.15372313  0.732930169  1.799095607  0.526507769
##  [108,]  0.790834481  1.61775851  1.391561092  0.302372127  0.537567014
##  [109,]  0.624708410  0.65250517  1.577181069  0.751942630  1.273842182
##  [110,]  1.009188717  0.67485068  1.731453366  2.009078649  3.742717598
##  [111,]  1.072543628  0.51832163  1.151011754  0.828635666  0.246984491
##  [112,]  1.382579461  0.37254256  1.874073981  1.339424759  0.410422922
##  [113,]  1.673272155  0.29723605  1.126330129  2.881659751  0.730843313
##  [114,]  0.537660767  0.28832686  0.705893315  1.695512859  0.545378378
##  [115,]  1.355996695  0.90504929  1.253590062  0.582882607  0.438877916
##  [116,]  2.764456139  0.41212654  0.531731499  2.053351595  1.312853409
##  [117,]  1.346870103  0.45137594  1.238958159  1.794266348  1.137740099
##  [118,]  0.609645693  0.55523590  0.600061553  0.833334944  1.071501857
##  [119,]  1.076750714  2.19989759  1.190954309  1.497731079  1.557932548
##  [120,]  1.895397854  1.31257474  1.528382741  2.012261775  2.314680869
##  [121,]  0.524931004  0.48890285  0.457312307  0.441466464  1.060963975
##  [122,]  0.085030063  2.05315708  1.332372212  0.067597578  0.428216372
##  [123,]  0.595595988  0.25989843  0.524630542  0.677173308  0.239353612
##  [124,]  2.252827441  0.79565551  1.604749669  2.984363550  0.803315006
##  [125,]  0.774836944  1.82722428  1.657427948  1.337526408  0.998598202
##  [126,]  0.383299862  0.82078272  1.084574440  0.379124142  0.663378329
##  [127,]  1.573901320  1.67136948  1.724235086  0.667891710  1.609886364
##  [128,]  1.001175247  0.39599034  2.307298573  2.998043682  0.832007414
##  [129,]  1.534439171  0.26456335  0.282019522  0.631746780  0.206676744
##  [130,]  0.550677329  0.72816148  0.691405035  0.513164088  0.673011045
##  [131,]  0.612401270  1.82020458  0.801153341  0.841462512  0.971115737
##  [132,]  0.237207712  0.69194082  0.860246364  1.037100368  0.594263494
##  [133,]  1.492044428 -0.07341695  1.115939248  0.158605793  1.644760376
##  [134,]  0.878082280  0.09281572  1.088148333  0.273339178  0.559311891
##  [135,]  0.630184238  2.17225966  1.965615057  1.640822428  0.690307316
##  [136,]  0.983912512  0.84958118  0.914265224  1.090424237  0.827186231
##  [137,]  1.050807731  0.20394024  3.005620177  0.674096985  0.732600308
##  [138,]  0.175229109  0.57579543  1.054494606  0.730532297  0.196641099
##  [139,]  1.564019697  0.36679060  2.552741639  0.972773831  1.200469517
##  [140,]  0.295337944  1.50352759  1.159491215  0.417808419  1.846316734
##  [141,]  0.217130545  0.89720144  0.997408151  1.074275918  1.615027553
##  [142,]  1.900594143  0.82257154  0.394975154  2.308244865  0.802425332
##  [143,]  0.731884519  0.94641850  1.117299643  0.177102130  0.205553610
##  [144,]  0.559427271  1.44877383  1.149053564  0.572468732  0.811502290
##  [145,]  0.781933558  0.74196081  0.460272765  1.159136769  0.853063573
##  [146,]  0.933537666  1.20433663  0.812580775  0.801877671  0.225234375
##  [147,]  0.534903695  2.03436391  2.790018895  1.072941096  0.243052286
##  [148,]  0.029437674  1.07191713  1.571322090  0.862258531  3.539013229
##  [149,]  0.817742142  0.31165780  1.406345264  0.840718191  0.959755010
##  [150,]  1.458928976  1.57810958  0.425977530 -0.028145408  1.644432819
##  [151,]  1.273364120  1.28609585  0.783558185  0.950335884  0.538951421
##  [152,]  1.034035797  1.30965026  0.230346260  0.547668537  0.473374075
##  [153,]  1.203593357  2.31118095  0.676334830  1.872724003  0.259068226
##  [154,]  1.410800692  0.14779316  1.234528321  0.445519531  0.351671748
##  [155,]  0.117741443  0.23088584  0.748943770  1.118356326  0.792742907
##  [156,]  0.486320922  0.18730596  1.356787512  0.717012792  0.909698765
##  [157,]  1.114362331  0.77768930  1.200929179  0.560224855  2.760884604
##  [158,]  0.332107642  3.44179757  0.881627333  1.364663992  0.135597832
##  [159,]  1.364835430  1.92619599  2.234407010  1.988153296  0.784104050
##  [160,]  0.748487993  0.40533975  0.150440368  0.168731866  0.335883799
##  [161,]  0.874279590  2.40154274  1.157962221  1.241524503  1.059142778
##  [162,]  0.444028658  0.17347528  0.044446632  0.652638057  0.199896585
##  [163,]  0.964174536  0.30821308  0.639025578  1.264035861  0.224131070
##  [164,]  0.147919955  1.17707105  1.164973237  1.280784579  1.251214482
##  [165,] -0.046331359  0.21528942  0.712046061  1.498226128  1.260521847
##  [166,]  1.061111527  0.60768249  1.750973066  0.543297640  0.445116782
##  [167,]  1.268457547  1.66023318  1.140494073  1.648988823  0.453851030
##  [168,]  0.780824226  1.83279148  0.138407076  0.926082234  0.936580922
##  [169,]  1.719324214  0.35460450  0.144739372  0.385390512  2.244936628
##  [170,]  0.430344933  0.22924746  1.109254475  0.760414267  0.459270507
##  [171,]  1.181642194  1.62290554  3.364255963  2.446262171  0.324071535
##  [172,]  1.989387967  1.80236204  1.694945792  1.143198158  1.007612862
##  [173,]  0.488906468  0.71462122  0.563549373  1.241377933  0.744551967
##  [174,]  1.346375573  0.55984016  1.126960102  0.662850958  1.081657956
##  [175,]  0.467303351  2.03321429  0.492747130  0.716864391  0.403513384
##  [176,]  0.976417924  0.93387906  0.531179296  0.966932520  1.263033234
##  [177,]  1.334118586  0.35500738  0.740792114  0.060487699  1.648670293
##  [178,]  0.371528406  2.18195487  1.457739951  0.561687722  0.822460038
##  [179,]  0.701031458  0.28290224  0.205112418  1.133779997  0.799131670
##  [180,]  0.811066094  0.34658605  0.309596200  0.921341678  0.166028247
##  [181,]  1.442690503  2.86861167  2.512180008  0.834949040  1.456626931
##  [182,]  2.279714010  0.42512361  0.727183195  2.026600106  1.039297253
##  [183,]  0.623103958  2.77635303  0.768795656  0.044515953  0.790975229
##  [184,]  1.265073147  1.14772882  0.923155955  1.322671746  0.674215711
##  [185,]  1.175658078  2.03554497  0.519581927  0.125792952  1.240706641
##  [186,]  0.046726772  2.22885336  1.352802687  0.145608413  2.163066415
##  [187,]  0.682399790  2.57138286  0.874062029  0.228822843  0.679650981
##  [188,]  0.211433320  0.53562246  0.402538091  1.625298155  0.415700307
##  [189,] -0.022450817  1.12861353  0.813622364  0.375449752  1.296069023
##  [190,]  0.640420953  0.08934773  1.301660929  1.097328668  1.565327168
##  [191,]  0.061177923  0.59087350  2.932446887  2.545468322  0.550873707
##  [192,]  1.119983076  1.26520422  0.739223617  2.444933563  0.971985391
##  [193,]  0.881801652  0.03195050  1.220080726  0.766506760  0.506658981
##  [194,]  3.909226267  0.81376542  1.625322899  1.124405324  1.039826037
##  [195,]  1.271994588  0.71672509  0.604108843  2.726840047  1.304421812
##  [196,]  0.334858740  1.35517831  0.327413084  1.533707807  1.027892443
##  [197,]  0.984977472  0.74128726  1.247255898  0.657246204  2.988613398
##  [198,]  2.075210693  0.43652155  0.912513894  1.056143589  0.600132778
##  [199,]  1.028822117  0.82540489  1.460918287  0.388299445  0.714258592
##  [200,]  0.314689200  0.20658338  0.563277869  1.208227837  1.040508805
##  [201,]  0.498464699  1.15763709  0.838758825  0.641037404  0.898676345
##  [202,]  0.260253818  0.19042525  2.424110378  0.954684781  0.708921361
##  [203,]  1.925239615  0.86778866  0.057946378  1.809306930  1.337045845
##  [204,]  1.304911475  0.73624219  0.087681202  0.659896384  1.550540837
##  [205,]  0.823642352  0.92936941  1.498359789  2.244581328  1.936985510
##  [206,]  1.515539371  0.98023588  0.893279608  1.146957692  2.812894250
##  [207,]  0.358288402  0.17334123  0.267122672  0.296979377  0.753580961
##  [208,]  0.527094866  1.26650316  0.201307026  0.424467740  2.107936050
##  [209,]  0.732251010  0.72318074  0.478522602  0.135782621  1.220085552
##  [210,]  0.567508968  0.35356489  1.494921576  1.815416046  1.204402646
##  [211,]  0.274404545  0.99896828  0.602297927  1.216106604  1.275189714
##  [212,]  0.262511133  0.88147971  0.946038755  1.724511827  0.646847079
##  [213,]  0.559848026  0.53214302  0.609762976  2.689249552  0.513256110
##  [214,]  0.705291995  0.77250007  1.010990552  1.099565896  0.777853084
##  [215,]  1.137174704  1.69970713  1.083721088  0.452691918  3.094779720
##  [216,]  0.411113237  1.42767576  1.301171559  2.310248246  0.499156292
##  [217,]  3.148093286  2.10702639  0.317688726  1.085394754  1.500921045
##  [218,]  1.321358184  0.79716268  0.198324902  0.890716862  0.816979909
##  [219,]  0.278047901  1.34362377  0.289553493  0.562904734  0.449542518
##  [220,]  1.387352370  3.36943571  2.083748312  1.351993005  0.656276243
##  [221,]  1.001177857  2.48900021  0.317388925  0.098572855  2.080182169
##  [222,]  1.742009687  1.08971913  1.363680463  0.835408800  4.673791860
##  [223,]  0.533477998  0.33994885  0.899348507  2.334378337  1.113403827
##  [224,]  1.526182000  1.73916229  1.469838845  1.046776372  0.346712797
##  [225,]  1.007553906  3.76291250  1.414778210  0.547925128  1.256583646
##  [226,]  0.505406557  1.61627176  0.988292898  0.459045748  0.714728361
##  [227,]  1.299792199  0.57328975  1.058648251  0.660763204  0.628102196
##  [228,]  1.558196236  1.19202232  0.735073942  1.170970573  0.154173648
##  [229,]  0.873792161  1.26409177  2.045140682  1.686305329  0.477605507
##  [230,]  1.048552980  1.04978722  1.321624678  1.959700302  0.693849587
##  [231,]  0.817654216  0.12919110  0.547387694  0.150008981  2.071219634
##  [232,]  0.640575433  0.52436002  0.983687932  0.031013674  0.287233990
##  [233,]  3.941641976  0.61819882  1.520331475  1.029102555  0.110681273
##  [234,]  0.045977046  0.33770047  0.683722912  0.065440515  1.372869680
##  [235,]  0.772632146  0.39257725  1.540997644  0.853834402 -0.072265892
##  [236,]  2.000187914  1.42325358  1.794060491  1.322786233  1.437034036
##  [237,]  0.470469591  0.78132708  0.498720574  1.299991473  0.476750818
##  [238,]  0.052042494  1.33536572  0.488692883  1.500455260  1.348400664
##  [239,]  1.090692196  0.17031703  1.524884702  1.269020416  0.596650411
##  [240,]  0.323395654  1.20167332  1.099442117  0.867361804  0.734061038
##  [241,]  0.837666154  1.21568425  1.280521603  0.394258485  1.722036271
##  [242,]  0.888152747  0.95402995  1.002539477  0.356513099  0.368929516
##  [243,]  0.972868963  1.61184004  1.630149862  1.183263977  0.856087806
##  [244,]  1.294630384  0.88345858  1.526314091  1.095780119  0.853040512
##  [245,]  0.444585303  0.75673343  0.787453684  0.621630964  1.103089292
##  [246,]  1.977974832  1.05489845  2.259468868  1.340245668  1.320195977
##  [247,]  0.865075057  1.30136379  0.912684193  2.870407793  0.546871331
##  [248,]  1.645744863  1.05287422  1.903182494  1.788211395  3.848899929
##  [249,]  0.473724372  0.98205030  0.414573142  1.028927000  1.305807367
##  [250,]  0.478433521  1.89064161  0.287266651  0.603153620  0.442784166
##  [251,]  0.986362761  1.34623924  0.705680604  2.004831415  1.750448789
##  [252,]  2.200625096  1.46242915  1.636601496  1.073763435  0.895551738
##  [253,]  1.378111389  0.25819857  1.351275692  2.135618046  0.965694702
##  [254,]  0.523087198  0.80925619  1.349475685  0.867901551  1.345357531
##  [255,]  0.997694590  2.10667217  1.202696504  1.637135437  2.699275089
##  [256,]  0.494128337  0.53499305  1.726028432  1.576797989  0.378286628
##  [257,]  0.318074978  0.62849006  0.476344491  1.763445936  2.177845333
##  [258,]  1.395104979  0.47997524  1.379638281  0.279055095  0.952090940
##  [259,]  0.567430897  1.89335170  2.062646089  1.084218691  1.165502456
##  [260,]  2.201246050  0.83125168  0.943293999  0.797076694  0.540850241
##  [261,]  0.652745741  0.84908056  0.563559442  0.418387930  0.435327476
##  [262,]  0.245717343  1.28389682  0.536969822  2.052264006  2.110222409
##  [263,]  2.759605886  1.31645227  1.328295989  0.832701392  0.633119589
##  [264,]  0.330690799  1.03009756  0.656553224  2.474476846  2.361870953
##  [265,]  2.338814847  1.30589689  2.248172690  0.491239177  0.487996994
##  [266,]  1.097475085  2.00694718  0.828301146  0.866544917  0.373660989
##  [267,]  0.687460038  0.86488221  0.113049836  0.336828687  1.593757568
##  [268,]  1.536012023  2.09493005  1.883399111  1.091583246  1.442085343
##  [269,]  1.076033356  1.26660816  0.756469780  0.567919392  0.657656020
##  [270,]  1.748580717  1.87438025  0.467388961  0.647475473  2.128674129
##  [271,]  3.433131028  0.82388651  1.271337304  0.487546965  0.965021048
##  [272,]  5.248397115  2.09856411  1.331356515  0.528301280  1.989694573
##  [273,]  0.658565841  1.40590394  0.306864005  0.902200781  1.088943130
##  [274,]  0.113819061  1.41375681  0.411532675  0.424369244  1.382901133
##  [275,]  0.923620875  0.78823684  0.422858317  0.371317517  0.169117513
##  [276,]  0.116678575  1.42599435  0.645870447  0.801218871  0.785680140
##  [277,]  1.250820582  0.86335556  0.637501937  1.718051882  2.299758421
##  [278,]  0.326281319  0.14543347  1.056373894  0.323240085  0.677092094
##  [279,]  0.552015017  1.35717833  1.569050240  3.082088772  0.917273736
##  [280,]  0.928030248  1.95454411  0.359889242  1.271496873  0.730335381
##  [281,]  0.360655699  0.66922339  0.693256027  0.105196244  0.489399046
##  [282,]  0.791883858  2.50701061  0.659713394  0.340241767  0.515219971
##  [283,] -0.009145462  0.34521701  2.802571456  0.111630056  1.750078711
##  [284,]  0.191485605  1.82783758  0.351277791  0.709068742  1.140656275
##  [285,]  0.246259460  2.16579557  0.797820471  0.260111565  0.986269271
##  [286,]  0.738252650  1.38767067  2.423663472  3.735044145  0.609236222
##  [287,]  0.049875485  3.09607049  1.093869776  0.355285245  0.463724575
##  [288,]  0.156832296  0.39782327  1.028411781  0.320453447 -0.047032540
##  [289,]  0.838350569  0.16520488  0.857140261  1.387237731  0.387753545
##  [290,]  0.470801267  1.38388508  0.744642922  1.327693028  0.357772648
##  [291,]  3.423620854  2.03065325  1.148869803  0.914603293  1.684982508
##  [292,]  1.052927207  1.26175950  0.813003634  3.461586470  0.459836723
##  [293,]  1.831027558  0.57319583  1.370538839  0.546552739  0.762123078
##  [294,]  0.471171396  0.45357027  1.275415076  1.212487588  0.848128380
##  [295,]  0.659888960  0.32641627  1.028930548  0.932047623  3.446418491
##  [296,]  1.936347552  2.51194113  1.985150165  0.378181193  1.776302699
##  [297,]  1.208332019  2.57076815  0.964663996 -0.192658208  0.913710795
##  [298,]  0.208021106  0.73741787  2.214930078  1.670323091  0.920205995
##  [299,]  0.115095339  1.00993370  1.038912326  0.396243601  0.524585946
##  [300,]  2.575517136  1.52823917  1.268881983  2.036406184  0.885753797
##  [301,]  0.016233214  1.65717678  1.043779281  0.463439116  0.347308672
##  [302,]  2.111320692  0.67618994  1.157397503  0.637871525  0.252712826
##  [303,]  0.565940305  1.32993684  0.554928098  0.261965804  0.382840282
##  [304,]  0.271885828  0.91890907  0.408513817  0.905025980  1.023628251
##  [305,]  1.620569999  0.84451824  1.188972941  0.137426221  0.591663715
##  [306,]  0.512455918  1.12837144  0.750524176  2.381090778  1.059279310
##  [307,]  0.689533876  2.44711323  0.401080450  0.239897925  0.841661536
##  [308,]  1.987169336  1.87624237  3.025348888  0.403400549  2.264300906
##  [309,]  0.867543107  0.59244119  0.327387373  0.469262496  0.251641828
##  [310,]  0.346353149  0.59211037  0.631902250  0.289937582  0.757115726
##  [311,]  1.849033975  0.80321262  0.951225572  0.823875333  2.627317336
##  [312,]  0.521291189  2.60530547  0.293630016  0.288742542  1.778804415
##  [313,]  0.570137845  1.02245609  0.829382240  1.409525973  1.237137353
##  [314,]  1.500166760  0.39975442  0.927534528  0.448232130  0.467371198
##  [315,]  0.664896918  0.25159250  0.900986834  1.250449722  1.246316402
##  [316,]  2.665898910  0.40368418  0.756177227  1.342702677  0.701702160
##  [317,]  0.044501466  0.98136022  0.423481880  0.573762881  0.428432589
##  [318,]  1.367453724  2.78908299  0.663228242  0.642847119  1.640650552
##  [319,]  1.807210744  0.93391883  2.249575658  1.186727339  2.943753212
##  [320,]  0.749109354  1.67682801  1.631495836  1.496052019  0.672484969
##  [321,]  0.876569950  0.12106182  1.123473568  0.616972106  1.409359012
##  [322,]  3.395335091  1.32479264  2.065338388  0.932901269  0.258283263
##  [323,]  1.970559769 -0.07300254  4.454438390  0.864772828  0.738003906
##  [324,]  2.116087042  1.86709059  0.747240823  3.573911185  0.942666196
##  [325,]  0.316170711  0.07327517  0.766545341  0.315067279  0.619026957
##  [326,]  0.255087585  1.06749756  0.190472150  1.160634312  0.353203423
##  [327,]  0.973194492  1.43758998  1.926926758  0.771967656  1.521435536
##  [328,]  0.991421778  1.50983380  0.452841026  1.107641641  0.305363627
##  [329,]  2.002333910  0.87731448  0.820410163  1.814683300  1.389470002
##  [330,]  0.623102509  0.01737947  0.344184970  0.088804943  1.399802074
##  [331,]  0.877128557  0.94127100  3.361849036  0.297712938  0.755786248
##  [332,]  2.167230183  1.09172711  0.631012195  0.504598859  0.546455581
##  [333,]  1.704909142  0.63346795  0.194942457  2.882711557  0.682826811
##  [334,]  0.878717513  0.46608191  1.720114947  1.652483479  1.273733878
##  [335,]  0.746904918  0.98316129  0.399394603  0.552414488  0.657899229
##  [336,]  0.190462066  1.41605873  0.915433797  0.085333548  1.045787464
##  [337,]  0.310961019  0.59839589  0.743116306  0.391051503  0.994795885
##  [338,]  0.590206979  0.62489462  1.892810285  0.657099502  0.823166382
##  [339,]  1.360847004  0.75061999  1.669700719  0.921422736  0.699379654
##  [340,]  0.551885800  0.69849305  0.597114915  0.894395119  0.523732755
##  [341,]  1.064401246 -0.06469004  0.390687374  0.343747654  1.141141366
##  [342,]  0.043180696  3.47537979  0.783162683  1.030938277  1.163253887
##  [343,]  1.229655134  0.73363046  1.519260683  1.121440746  0.593861574
##  [344,]  0.975548292  0.42871748  1.507881719  0.213360802  0.444770495
##  [345,]  0.082523601  0.38519216  0.130604084  0.235694979  0.658771592
##  [346,]  0.493963269  1.28369419  1.125073171  0.626085936  1.319957702
##  [347,]  0.606891774  0.28346828  1.418532288  1.669290140  0.810532500
##  [348,]  0.888872824  0.17601415  1.252686866  0.802604941  1.843965569
##  [349,]  0.829553465  1.73683825  1.059582632  0.700774213  1.133622048
##  [350,]  1.200377974  1.31447999  0.773034485  1.521339687  0.599808347
##  [351,]  0.347616869  0.62825016  0.288329284  1.657029744  0.318295117
##  [352,]  1.277399410  2.13201812  0.254270334  0.689644622  0.804993211
##  [353,]  0.868577153  2.16120880  0.642528179  1.331870923  1.093541357
##  [354,]  1.056980539  0.41135004  2.067675202  1.251498738  2.145847989
##  [355,]  1.338472717  0.84694462  0.834926518  0.673280803  0.811014861
##  [356,]  0.529707854  0.59078633  0.909084417  1.069736308  0.415689625
##  [357,]  0.699108984  0.87367082  0.639546678  0.068077263  0.365850543
##  [358,]  0.254883909  0.81579582  1.287882496  1.439876926  1.856379626
##  [359,]  0.414953676  2.19603664  0.789489407  2.801997272  1.903720848
##  [360,]  0.449907962  2.64520925  0.871958605  1.120293318  1.222478172
##  [361,]  0.786221897  0.82357560  1.233269941  1.698936331  0.637280433
##  [362,]  0.949719683  1.66712263  1.546197970  1.299940563  0.656046104
##  [363,]  0.149956512  0.48443208  0.714579652  0.563572583  0.805086164
##  [364,]  1.607217484  4.07259017  2.752152933  0.366448961  1.342095848
##  [365,]  1.067409035  1.73397659  1.637527392  0.050072024  1.241752587
##  [366,]  1.233492958  0.32821277  1.471062800  0.450477562  0.083021855
##  [367,]  0.634972495  2.57182999  1.850568135  0.684503787  0.175864430
##  [368,]  2.050893091  0.56998465  0.083271798  1.045555339  1.085465382
##  [369,]  4.542305165  1.05864837  2.149898306  2.144721058  1.646342196
##  [370,]  0.272770012  0.71386082  0.601876973  1.394152254  1.221896918
##  [371,]  1.087477014  0.61878695  0.730013477  0.492540746  1.237665021
##  [372,]  0.654782657  0.34203886  0.079267482  0.691780494  0.592966820
##  [373,]  1.768202982  0.99159624  1.835990870  0.726910944  2.220863532
##  [374,]  0.713764818  0.71400318  1.104904844  0.480901535  1.611536353
##  [375,]  0.725858657  0.63093829  1.242756650  0.660057444  0.961153772
##  [376,]  0.181122888  1.24864380  0.507323580  0.901061045  0.373594865
##  [377,]  0.379966701  0.49275802  0.938710000  0.274666008  1.451259847
##  [378,]  0.427728279  1.45689684  0.342166980  0.697478255  2.129192980
##  [379,]  0.996399564  0.75268867  0.753356238  0.483032234  1.463716922
##  [380,]  1.254507245  1.65113404  0.152785194  0.752850601  1.061916220
##  [381,]  1.813531577  0.38501346  1.281638462  1.127741469  1.229728309
##  [382,]  2.033948950  0.89541183  0.174655667  0.536197393  1.636379471
##  [383,]  1.323668492  4.03686460  1.273411503  1.020118793  0.203787951
##  [384,]  0.597146246  0.75803013  0.341710823  1.662988202  1.179241155
##  [385,]  2.455659544 -0.05539079  1.130376057  0.860253367  0.749405607
##  [386,]  3.375046550  1.89335179  1.431344996  1.036362482  1.505876861
##  [387,]  1.538599151  1.66386032  1.545077732  1.180710910  0.358418049
##  [388,]  0.676640737  0.90441295  0.622177238  1.686186654  1.104536989
##  [389,]  2.224607317  0.43367377  0.101341301  0.617552399  3.052670910
##  [390,]  1.387157767  0.34243227  0.567644191  0.203567613  0.700783003
##  [391,]  0.610303387  1.15291224  2.167355249  1.130115286  0.945143336
##  [392,]  0.436713610  1.79734234  1.021838967  0.938505413  1.349463444
##  [393,]  0.209173395  0.21740686  0.541042433  1.830845573  0.257623826
##  [394,]  0.784786986  0.75209658  0.515277165  1.504083779  0.670490749
##  [395,]  2.358222398  1.13372397  0.729782231  1.163924397  0.804680867
##  [396,]  1.120220509  0.97620048  1.268767815  0.930899055  1.446772213
##  [397,] -0.084138939  0.24250767  0.869883042  0.253300312  0.640138211
##  [398,]  0.596387352  0.48562466  1.497076092  2.075587996  2.362540974
##  [399,]  0.516951327  1.29720574  0.291957409  0.555805600  0.399800728
##  [400,]  0.718011310  1.67941442  0.655843986  0.691442109  1.340833458
##  [401,]  1.497274844  0.64840523  1.516268569  2.285738909  0.655249498
##  [402,]  1.207759803  0.19440768  0.124233131  0.844740614  1.365564238
##  [403,]  1.819458273  1.06777324  0.534581200  0.214277654  0.639500570
##  [404,]  0.219115782  1.22009972  0.198664427  1.302797819  0.540881017
##  [405,]  0.124924376  0.78949537  0.396952516  1.545177776  1.871939616
##  [406,]  1.404630221  0.20653349  0.122520408 -0.110604080  0.318246585
##  [407,]  0.847557089  0.18185627  0.726440921  1.445525717  0.020216955
##  [408,]  0.380638820  1.48371741  0.406770417  1.330004650  0.306896745
##  [409,]  0.064504084  0.78335012  0.747759323  1.254952526  0.533270846
##  [410,]  1.678222689  1.60030930  0.469397723  1.599240191  0.160987843
##  [411,]  0.698072163  0.22069180  0.820173522  1.750420878  0.422093419
##  [412,]  1.688288000  1.13076544  5.096545347  1.319512311  0.801763844
##  [413,]  0.272114511  1.45580918  1.443464585  0.673996943  0.977749313
##  [414,]  0.603026200  1.45239467  1.612083728  0.731312818  2.670169137
##  [415,]  0.324484879  0.73276758  0.251704111  0.409959013  1.111905540
##  [416,]  0.365337815  1.82619821  1.582358771  0.498096745  0.392740152
##  [417,]  0.323541736  1.16813519  1.792599062  0.680742069  2.685606339
##  [418,]  1.548019919  0.83170088  1.061366950  0.573998171  0.203588946
##  [419,]  1.197274433  0.31828601  2.032391861  0.297419467  0.506814307
##  [420,]  0.894325172  1.47324407  0.875492130  1.290568574  1.303302867
##  [421,]  0.080928640  0.23070294  1.063348464  1.005399455  0.137551119
##  [422,]  0.610545887  0.45131643  0.878464821  1.486996956  0.161119410
##  [423,]  1.502630479  1.69298377  1.726372772  1.395956054  0.561851228
##  [424,]  0.934085703  0.46271353  0.380865443  0.968971484  2.302288171
##  [425,]  0.921551646  0.39796622  1.617511165  2.387623526  4.138964196
##  [426,]  0.610682092  0.98442357  2.266667254  0.203524568  3.283872760
##  [427,]  1.335298314  0.66927227  1.391379531  0.553739380  0.701538070
##  [428,]  0.665995898  0.86875646  0.509864038  1.184870657  0.851475758
##  [429,]  0.334003487  0.63640174  1.600320842  0.647951449  1.437663297
##  [430,]  0.654376658  0.27427438  1.674570676  2.418790324  0.942352802
##  [431,]  0.378032812  0.56402474  0.353668733  0.704942260  0.705531855
##  [432,]  1.961250777  0.59817563  1.602627240  0.419145845  0.899644863
##  [433,]  1.620381890  0.50614277  0.450895359  1.000447071  1.172048965
##  [434,]  0.106872955  1.26140995  0.308570444  1.096710788  0.970284470
##  [435,]  1.439925753  1.39718701  0.756250597  1.093919787  0.889405103
##  [436,]  0.754093101  0.26393077  0.097620034  0.608935393  0.449407286
##  [437,]  0.318907582  0.41493799  0.561459601  0.744533755  1.118845734
##  [438,]  0.917853683  0.62533734  0.959731631  0.088307200  0.354115870
##  [439,]  1.094308493  2.97201569  1.973376960  2.107693482  1.216627007
##  [440,]  0.600762873  0.91743689  2.179722451  0.410974635  0.775516604
##  [441,]  0.896785937  1.16413233  0.987756455  0.393682894  0.945305539
##  [442,]  0.901238899  1.11051553  0.456335213 -0.061549959  1.623363348
##  [443,]  0.504160222  0.50961238  0.338161738  1.239766760  1.122329922
##  [444,]  0.663804269  0.46848856  0.713723207  1.094335241  0.555626327
##  [445,]  0.116397161  0.77901042  1.103334898  0.552878196  1.086335102
##  [446,]  0.875940234  0.56971741  0.335898993  0.464265691  1.608082309
##  [447,]  0.263298725  0.95838162  0.334233418  0.374027988  0.628111662
##  [448,]  1.404753472  2.51233936  1.910539391  0.182799062  0.815100244
##  [449,]  0.561342629  1.12447162  2.216466242  2.364933418  1.613077599
##  [450,]  0.211667450  0.39621112  0.137749273  0.945143662  0.955083021
##  [451,]  0.903707170  1.24900910  2.259560086  1.622255518  1.303582700
##  [452,]  1.175431479  1.25477652  0.060466160  3.356528000  1.333725593
##  [453,]  2.680139258  1.31946106  1.627167791  0.844585960  1.711970342
##  [454,]  0.053432361  0.90710911  1.415996619  1.673256060  0.929808978
##  [455,]  1.060277871  0.08860473  0.147782192  0.949284014  0.859636848
##  [456,]  1.253096165  1.71777160  0.532988934  0.067058731  0.873136356
##  [457,]  0.519199305  0.54069421  0.715163717  0.997285911  1.603841171
##  [458,]  0.827723244  0.62497632  2.062924783  1.367116496  0.969286422
##  [459,]  0.184956424  1.06912676  0.463479103  0.372361120  1.470194875
##  [460,]  1.037793486  0.57424833  0.885928429  0.380167317  1.170088252
##  [461,]  1.293202417  0.23030694  0.363972008  0.827739416  2.403629171
##  [462,]  1.539086789  1.30435597  1.338680363  0.706584593  0.027418513
##  [463,]  0.464332795  0.18645461  1.383402186  1.353433202  1.981937495
##  [464,]  1.973398642  1.22127126  0.857372711  0.986128947  1.527440944
##  [465,]  0.633463650  1.94164009  1.229282636  0.892502874  0.372938082
##  [466,]  1.784337028  0.75791963  1.213246946  0.093129163  0.475116663
##  [467,]  0.322530549  0.29480633  0.793856181  0.491715860  0.724711753
##  [468,]  0.392172455  0.31331454  2.410905311  0.690907339  0.602295861
##  [469,]  1.167656620  1.07100717  0.991804921  1.560112739  1.454484422
##  [470,]  0.721777180  1.26055392  0.628439390  0.373108885  1.332835887
##  [471,]  0.441400148  0.19762617  0.502745508  1.505339768  0.580018411
##  [472,]  1.815387460  0.57328888  1.130918360  0.579627117  0.583779020
##  [473,]  1.155794594  1.12401754  0.516846749  2.358300959  1.009354359
##  [474,]  0.336578796  2.03793733  1.490897133  0.907908046  2.130455640
##  [475,]  0.769365381  0.85075301  0.282024115  0.389798991  1.087118068
##  [476,]  1.712670661  0.84878959  2.323129733  0.626440483  0.924657771
##  [477,]  0.781514362  0.49797868  1.115641798  0.191506907  1.073927612
##  [478,]  1.371413776  0.45567714  0.316395865  2.367052337  0.783649801
##  [479,]  2.565476164  1.81342844  1.929061941  0.961947645  1.091216955
##  [480,]  0.900500105  1.10936814  2.418992339  1.466700854  0.578045200
##  [481,]  0.655514640  0.99666015  0.397815464  2.018304855  0.555283565
##  [482,]  0.474161175  1.33902784  0.210041196  1.053520421  1.500803708
##  [483,]  2.513161091  0.63007069  0.193029183  1.066781303  0.411130414
##  [484,]  0.645311115  1.50486768  0.085911444  3.347081249  0.831719365
##  [485,]  0.248501493  0.30001016  1.094879086  0.665950488  1.752754128
##  [486,]  0.548791534  0.21831755  0.876986309  1.582628669  1.387037188
##  [487,]  0.426344522  1.25316456  0.376690076  0.014301507  1.034285084
##  [488,]  0.999446517  0.59990205  2.197160009  0.306273187  1.557879145
##  [489,]  1.009894548  1.84434009  0.360068517  0.650065021  0.041182570
##  [490,]  0.982959874  1.06023119  0.570792076  0.220745644  0.122949512
##  [491,]  0.952294527  0.66455830  0.593669241  1.308163662  1.425734622
##  [492,]  0.389758896  2.13939055  0.174018796  2.305075237  0.153927541
##  [493,]  2.711270068  0.89100666  1.100406155  2.512990877  1.783862810
##  [494,]  2.832418031  1.62498549  1.078897764  0.605707437  0.784592567
##  [495,]  0.809042839  3.60554273  1.384187473  1.561220778  0.439133160
##  [496,]  0.298354115  1.53398889  1.655936138  1.654635244  1.795726979
##  [497,]  0.801235197  0.73292735  0.775431892  1.595137371  1.423126694
##  [498,]  0.410662607  0.76652022  2.510806986  1.623082201  1.318207010
##  [499,]  1.294455400  0.43728694  0.952311771  0.197084706  0.763409515
##  [500,]  0.747331810  2.05490179  2.144799515  1.622213178  0.191478043
##  [501,]  0.445521677  2.10071931  1.574708750  0.566720013  1.482585487
##  [502,]  0.986866830  0.54377322  1.148341250  1.104427719  0.188913011
##  [503,]  0.492258879  0.86671598  0.078886704  0.761908789  1.959681017
##  [504,]  1.136243362  0.52713013  0.860597358  0.493010234  0.923772786
##  [505,]  0.108421376  1.81880066  1.342347657  0.944849380  0.867308896
##  [506,]  0.549358909  2.67874543  0.390829459  0.775678499  1.064576126
##  [507,]  2.176914604  2.54955561  0.184033910  0.406930420  0.490119604
##  [508,]  0.716217164  0.84162633  1.336480872  0.901661260  1.381898565
##  [509,]  0.545250817  0.56993084  0.943409490  1.231234591  0.766911451
##  [510,]  1.454347718  0.90133311  0.450063248  2.424106062  1.086584307
##  [511,]  0.771308014  0.38880537  0.260553423  0.945144521  0.609146129
##  [512,]  1.016577066  0.35390760  0.251524924 -0.025595983  0.657815998
##  [513,]  1.443566702  0.17038498  1.274068665  1.170161910  0.230069669
##  [514,]  0.999471089  0.92914969  0.950075269  0.165374759  0.745518592
##  [515,]  1.524666152  0.22953602  1.606681121  2.086556492  1.364343981
##  [516,]  0.604612141  0.69921063  0.798838313  1.968832307  0.504070525
##  [517,]  0.319401008  0.40954112  0.111431467  0.742603280  1.361015500
##  [518,]  2.715269792  0.74501936  0.272615687  0.983965293  0.559961011
##  [519,] -0.059494349  1.49655631  1.500875406  2.120711709  0.325564090
##  [520,]  0.004489165  3.48726089  0.187036810  1.014936960  0.594211806
##  [521,]  0.941941081  0.93601856  1.100256513  1.097870822  0.611269650
##  [522,]  1.289782847  0.25975078  1.786975761 -0.017510557  1.171013641
##  [523,]  1.855110418  1.34658278  2.328641397  0.381979499  0.398419719
##  [524,]  0.200849090  4.61123076  1.198800438  3.206105666  0.281494301
##  [525,] -0.123572844  0.41975663  0.356530939  0.613196975  0.387693825
##  [526,]  0.421642465  0.68998345  0.836909280  0.219960992  0.535825777
##  [527,]  2.859982661  0.62029987  1.707738111  1.308078427  0.059225515
##  [528,]  0.175209507  1.10054447  0.130373240  0.932552869  0.365427475
##  [529,]  1.568188618  0.53150656  1.398994419  0.238495648  0.255755229
##  [530,]  2.947018832  1.28948665  3.025404285  2.700142386  1.421911118
##  [531,]  1.353026635  1.25234440  0.527336605  1.214988582  0.811891979
##  [532,]  1.664586044  0.85421211  1.022440133  1.107590997  1.851636207
##  [533,]  0.637021783  1.10487939  1.513588732  1.438815758  1.383946730
##  [534,]  1.088316749  1.18644044  2.309795908  0.345065578  0.474052124
##  [535,]  0.161081151  1.25999873  1.474774047  0.749911898  1.719308373
##  [536,]  0.701049233  0.90082301  0.396273608  1.277031359  0.944124394
##  [537,]  1.226303185  1.22547668  0.981553780  0.703958203  0.420725304
##  [538,]  0.766974311  0.40519396  0.437530979  1.096140069  0.549793637
##  [539,]  0.622803185  1.21970569  0.833168018  1.637710458  0.815436820
##  [540,]  1.850336456  1.67003218  0.465543598  1.844281987  0.665489915
##  [541,]  0.953765675  3.32350134  1.177431865  0.223776864  0.969654185
##  [542,]  0.896175472  0.40906861  2.109577374  0.756032841  0.513896353
##  [543,]  1.311069047  0.94830078  0.613249570  1.008178807  1.072272384
##  [544,]  0.623638237  1.28114770  1.024348836  0.585715627  0.798802582
##  [545,]  0.430127161  0.63617653  0.742120505  0.702429175  0.004958808
##  [546,]  0.957422506  0.15308859  0.902642935  1.446389253  1.098390145
##  [547,]  0.119623077  0.85517914  0.712894268  0.492237078  0.635360416
##  [548,]  0.597942590  0.30559836  1.135898587  3.741975691  1.269508847
##  [549,]  0.588279266  0.53669480  0.674422199  0.677609809  1.316850145
##  [550,] -0.065068735  1.25915896  1.054736516  1.330046879  1.171040664
##  [551,]  1.142123301  2.61567493  0.578035976  1.698284357  0.921328571
##  [552,]  1.238889371  2.11548199  0.316802948  1.520649693  0.033657844
##  [553,]  0.764166324  0.53831944  0.376300995  0.886012718  0.695449869
##  [554,]  0.324080381  0.90187373  2.153604863  0.558404583  2.107362210
##  [555,]  1.544796126  0.95548561  0.094360520  1.722145642  0.506743460
##  [556,]  1.363163932  0.48580554  1.188501594  2.147358873  1.120239214
##  [557,]  0.562645552  2.08047750  0.400263552  1.192290242  1.536774036
##  [558,]  0.854423664  0.75796855  0.600597793  0.364884718  1.331292974
##  [559,]  1.859919335  1.21863707  0.571948799  0.948527811  0.038343720
##  [560,]  1.353796134  0.84002820  0.331515353  0.630077401  0.624325241
##  [561,]  0.384690306  1.39437383  0.660849632  0.583168727  0.478383841
##  [562,]  0.803905491  0.39451882  1.676070572  1.470310040  0.243797969
##  [563,]  1.030019332  1.21912175  1.147265276  0.976508506  0.107505277
##  [564,]  1.301018363  1.22428422  1.385371822  1.937112098  0.605947810
##  [565,]  2.013826959  0.41955533  0.183601832  2.070950439  2.112678639
##  [566,]  1.762123344  0.45527425  0.554700268  0.926882723  0.136646657
##  [567,]  0.392768371  1.46204107  4.050200863  0.420032903  0.739223408
##  [568,]  0.342380969  0.52977636  0.877561852  0.270768279  2.072717622
##  [569,]  0.422848712  0.91685470  1.642631155  0.485232666  0.410483203
##  [570,]  1.505287281  0.27357200  0.783226807  0.387452469  0.216422013
##  [571,]  0.461634701  0.43581871  0.652749521  1.193830615  1.326173373
##  [572,]  6.827171899  0.79595195  1.936275310  1.817994277  1.763503334
##  [573,]  0.686912328  1.43105745  0.533410981  2.239063849  1.740112655
##  [574,]  0.899896382  0.56320575  0.601900409  0.293998565  1.285692736
##  [575,]  0.294522194  1.57252541  1.384902628  1.525773838  0.506816509
##  [576,]  3.719933861  1.10008499  1.017660283  1.216921866  2.329778015
##  [577,]  0.679494766  0.72653475  2.167674510  0.718308183  0.036840132
##  [578,]  0.164690931  0.42007972  0.643758489  0.595609062  0.541315320
##  [579,]  2.426237057  2.04080601  0.124523161  0.899379796  0.839770405
##  [580,]  0.512617819  0.69842747  0.593719674  1.771634910  0.397581855
##  [581,]  1.904514495  0.62701734  0.118929807  3.743736527  0.564696028
##  [582,]  0.461538815  1.70328025  0.702163819  0.831186145  1.875056320
##  [583,]  2.443088618  0.83698606  0.892505493  0.362067767  0.231697152
##  [584,]  0.807276329  0.86530982  1.865738767  1.546537212  0.862792200
##  [585,]  0.617690804  0.18737275  0.618148586  1.930518015  1.650904242
##  [586,]  0.336315356  1.12616619  1.178501972  0.407713655  1.099796771
##  [587,]  0.102927171  2.37770633  2.375803723  3.211355851  1.529705031
##  [588,]  0.589266831  0.13590623  0.507259239  0.506832572  1.142413634
##  [589,]  0.906509999  0.52067060  0.630614509  1.575853757  0.852007730
##  [590,]  0.639039863  0.05858754  1.368905856  1.075031468  1.318960900
##  [591,]  0.681447493  1.99537549  1.167352359  1.009829387  1.054299208
##  [592,]  0.471372093  1.49173665  0.469380832  2.217118845  0.252872742
##  [593,]  1.157285946  0.94715424  1.380047117  2.282722502  0.120837964
##  [594,]  0.659388650  2.07582386  2.286179070  1.549923470  1.546041613
##  [595,]  0.164057529  0.21110317  0.905866405  0.346561465  0.686643237
##  [596,]  1.065765628  1.63678494  1.292315281  0.634823366  0.460891682
##  [597,]  0.779972226  2.67224094  1.929377493  2.354305268  0.499373188
##  [598,]  1.431686720  0.68205844  0.883778343  1.620805334  1.066503099
##  [599,]  0.782053179  1.47504526  0.688099816  0.125597338  0.723940800
##  [600,]  1.468355477  1.30862679  0.429864455  0.524961699  1.617759385
##  [601,]  0.455008754  0.48368405  1.100839760  0.595349978  0.266750086
##  [602,]  0.044620899  1.29657099  1.445203644  0.658447298  0.300476530
##  [603,]  0.976476872  1.74215576  1.905436505  0.510474698  0.332049120
##  [604,]  1.936111486  1.26273818  0.439104386  1.100089850  0.145742283
##  [605,]  2.079330325  0.51565917  0.299327794  0.577117585  2.160390807
##  [606,]  0.055095379  2.12727861  0.373431149  0.627269616  2.053077656
##  [607,]  4.002702115  1.65757278  1.107071294  1.769159487  0.401656613
##  [608,]  0.381735967 -0.10966903  0.896854021  0.880508907  0.735166524
##  [609,]  0.572364077  1.13356375  0.979481560  0.750466578  0.968729890
##  [610,]  1.142720658  0.59439768  0.795420504  0.489030533  1.453028423
##  [611,]  0.342085892  0.47227615  0.434453335  1.484826445  0.296425411
##  [612,]  3.038939510  1.37887532  2.476047215  0.396524921  2.109250150
##  [613,]  1.367014507  3.43259351  2.287668891  0.123131409  0.983199468
##  [614,] -0.010046243  1.55589776  0.830514591  0.206933283  0.982366900
##  [615,]  1.088048685  0.49163179  1.890484159  0.821277719  0.344260980
##  [616,]  1.362707202  0.66890394  1.423907378  1.735487655  0.063839344
##  [617,]  3.504685442  2.13226108  0.619580582  0.636329835  0.184107715
##  [618,]  3.324133883  0.36978125  0.893830831  1.166166514  0.789392043
##  [619,]  0.738176002  0.31730163  0.173273798  1.470698733  1.054160041
##  [620,]  0.805984018  1.57202486  0.881331417  1.780008700  3.003641864
##  [621,]  1.184521449  1.61270423  1.099180369  0.638247757  0.948181159
##  [622,]  1.279389230  0.72437843  1.602241599  0.259908008  1.895989132
##  [623,]  2.602215974  1.18256589  1.993279345  0.264198717  0.830055037
##  [624,]  0.143250581  0.65100132  0.292755103  1.477790876  3.700405484
##  [625,]  0.811127590  0.63052528  1.246634018  0.514143299  1.715524786
##  [626,]  0.458981073  0.57378713  1.991280611  0.919944532  2.597064379
##  [627,]  3.525336932  1.56049858  0.455338403  0.731536776  1.222323822
##  [628,]  0.506925069  0.41480254  0.306487936  1.031885845  0.091442714
##  [629,]  0.246820451  0.63322527  1.056836383  0.338677060  0.538416114
##  [630,]  4.203447190  2.30019580  0.708937632  0.060839002  0.508392439
##  [631,]  0.225022958  0.47367561  1.675290864  0.880958554  0.843816618
##  [632,]  0.627769593  0.67052469  2.344306685  1.682373287  0.291492350
##  [633,]  1.048267228  0.72314523  0.427835274  0.429770044  0.520241808
##  [634,]  1.576550197  0.63254208  1.914152000  1.447123959  1.072482810
##  [635,]  0.239490116  1.33954863  0.479610318  1.000560583  1.639438489
##  [636,]  0.943386896  0.66607195  0.990842263  0.606723571  0.912251337
##  [637,]  0.379535338  1.42600929  0.891156607  1.027884092  1.501336722
##  [638,]  0.413985944  0.65097813  2.386103151  1.313965406  0.591501995
##  [639,]  1.969489096  0.91393629  0.124183865  0.997064691  1.053930648
##  [640,]  2.172827528  1.28152750  0.256079628  0.561320035  0.841656340
##  [641,]  0.366205409  0.16467147  0.437940004  0.475125016  0.604432749
##  [642,]  1.120109911  1.07092907  1.118915995  2.123920758  0.833590370
##  [643,]  1.228413652  1.76039271  0.510754144  0.376211535  0.562357244
##  [644,]  0.980773238  3.07858767  0.813461185  0.786048664  0.486989482
##  [645,]  1.505376642  0.88838529  0.737621755  0.613103787  1.382159077
##  [646,]  1.720801939  0.26734713  1.407425021  0.900392994  1.996624111
##  [647,]  0.608182865  0.26265035  2.017578727  1.173227661  0.576404192
##  [648,]  0.187502505  0.04016970  1.095179348  1.277752232  0.634715817
##  [649,]  1.336255931  1.07751838  1.407088799  0.823570713  2.511559617
##  [650,]  1.657504279  0.54216921  1.447771117  0.647427510  1.208249637
##  [651,]  0.955159282  0.74416937  0.976616878  1.847320719  1.168357433
##  [652,]  1.582488914  1.86906401  0.142754560  0.695803887 -0.049934105
##  [653,]  0.795655662  1.07450847  1.242181855  0.922166106  0.224994885
##  [654,]  0.196947231  0.79011107  1.091530012  2.027733426  1.253763796
##  [655,]  0.225007279  1.01623522  1.503025110  0.530971528  0.568356076
##  [656,]  0.559372377  1.02863520  1.256231809  0.710690795  1.220740579
##  [657,]  1.101334519  0.87063656  0.519335931  0.306686523  0.642260710
##  [658,]  0.199820305  1.79357296  0.391297008  1.584337457  0.825835273
##  [659,]  0.077894422  1.30514915  1.426592099  0.996284795  0.240881995
##  [660,]  1.046811728  0.73582830  1.592073017  0.298521770  0.235296511
##  [661,]  1.189145798 -0.16370437  0.381086134  0.996804815  0.422022900
##  [662,]  0.308365268  1.50842557  0.225863487  1.950119156  3.477643576
##  [663,]  1.453598684  0.47445211  1.181752738  1.644962517  0.403661573
##  [664,]  1.199208584  1.52276854  1.891008505  0.502685977  2.281575910
##  [665,]  0.535600077  0.67612903  0.628751078  0.332043801  0.561567494
##  [666,]  0.837905042  0.49402544  0.348826844  2.042576561  0.448634432
##  [667,] -0.046670684  1.91584850  0.992937802 -0.004031198  1.094220977
##  [668,]  0.796795641 -0.03790852  1.907317476  1.661557509  1.789844120
##  [669,]  2.031391012  0.14101567  0.007737943  0.164314917  0.867127144
##  [670,]  0.404118460  2.13425391  1.953136746  1.826275215  1.443430269
##  [671,]  1.131288981  1.85381473  1.130187474  1.119212999  1.871103846
##  [672,]  0.187527673  0.63937981  0.816174117  2.507955863  1.668960816
##  [673,]  0.719606192  1.06935450  0.818074415  0.525769750  2.798491020
##  [674,]  0.811749144  2.58940384  0.463840623  0.394190602  0.986710186
##  [675,]  0.105654958  2.93699327  0.308453829  0.081564927  2.019514246
##  [676,]  1.743032536  0.99657905  0.958466329  2.039405944  0.222465903
##  [677,]  0.092385466  0.18695894  0.913273522  1.417577513  1.484288694
##  [678,]  0.610731699  1.14459298  0.658550223  1.275342929  1.585842556
##  [679,]  0.249578106  1.76543871  0.457554748  1.971467305  1.381532866
##  [680,]  1.651712181  0.69874795  0.540041422  0.492825960  0.166962680
##  [681,]  0.969191412  0.36851795  0.917312975  0.025262632  1.114960374
##  [682,]  0.444731978  2.37903832  0.848790479  3.797283837  3.193942044
##  [683,]  0.306220705  0.49917407  0.140027093  0.716201506  0.353858220
##  [684,]  0.808796592  0.43177839  0.430541476  0.894533897  0.108612329
##  [685,]  0.757383701  0.26177094  1.090427116  0.730722615  1.892844523
##  [686,]  1.372741287  0.89744262  1.189666762  0.940784594  3.894605943
##  [687,]  1.348182711  1.47340604  1.026287276  1.825654538  2.668051272
##  [688,]  1.458263316  0.52465413 -0.079531898  1.720741364  2.438302188
##  [689,]  1.285041029  0.45045856  1.168938862  2.341827960  0.449965372
##  [690,]  1.952129573  0.76008491  0.916279960  0.200416883  1.452022316
##  [691,]  0.409272362  1.18144984  1.018943713  1.671530780  3.510577681
##  [692,]  1.391921063  1.60880030  0.554083449  3.023254089  0.819954724
##  [693,]  0.798904829  1.76658351  1.532113201  1.097711884  0.978474177
##  [694,]  0.920789161  0.19759517  0.188845140  0.333059806  0.686671677
##  [695,]  1.062905711  1.75801883  0.849640883  0.833517786  0.437936461
##  [696,]  0.336261518  1.37876633  0.037783902  0.818636728  0.799599272
##  [697,]  1.038033328  1.91501498  0.995797562  0.639161505  2.066943732
##  [698,]  1.529599218  0.21733167  1.191676230  0.981524850  1.895985085
##  [699,]  0.420994654  0.31558632  2.091186732  0.543659385  1.459212910
##  [700,]  0.753796853  0.65081717  0.479621568  0.367682890  0.914424427
##  [701,]  0.595736722  2.36714767  1.901116208  1.078606026  1.267649283
##  [702,]  1.403853124  0.46010310  1.159516648  0.942067176  2.867356962
##  [703,]  0.122585254  0.36595510  0.626651053  1.372291411  0.590894999
##  [704,] -0.170573922  2.73193678  0.340105192  0.580220266  0.746789999
##  [705,]  1.277315913  0.59664477  0.436536352  0.440918290  0.325985269
##  [706,]  1.093237302  1.48416385  0.925026718  1.067486233  0.269699106
##  [707,]  0.414048789  1.47467831  0.794698649  0.043492154  0.310966217
##  [708,]  2.108054086  1.31573265  0.386912573  1.267301763  0.400605837
##  [709,]  0.675236333  2.42373797  0.681962596  0.150674960  0.917920014
##  [710,]  0.208019129  1.12780617  0.401810002  0.845205619  1.205563560
##  [711,]  4.412080754  0.99985938  1.429500580  2.729790084  0.621973450
##  [712,]  2.492891020  1.10759094  3.168772440  1.274701943  1.518346744
##  [713,]  0.123317112  0.20883789  0.340018605  1.708675680  0.263989308
##  [714,]  0.822386429  0.66026793  2.427521450  0.799678793  0.382470719
##  [715,]  1.308703296  2.16853273  1.157754509  0.359000273  0.329666077
##  [716,]  0.975403285  0.71914784  1.018522146  0.457222423  0.965691387
##  [717,]  0.137817801  0.61574545  1.771736203  0.884415084  0.729732672
##  [718,]  1.251534312  3.06883032  1.030168997  0.936076662  1.311271536
##  [719,]  0.703736178  0.29608205  1.637646425  0.025961756  0.364800329
##  [720,]  0.440626113  0.71156613  0.573984334  0.078580984  1.645626318
##  [721,]  2.393534170  1.02656899  0.814641736  1.273087843  0.358275027
##  [722,]  1.107387558  2.68350237  0.698800040  1.196734203  0.712752147
##  [723,]  1.174130008  0.95520302  0.603848692  1.634023002  0.831781147
##  [724,]  0.918580168  1.11182641  0.937943047  0.278123947  0.624800781
##  [725,]  0.099397164  0.75810419  1.139599132  1.134773302  0.262502699
##  [726,]  0.977769936  2.50955454  0.549661544  0.247447096  0.211096760
##  [727,]  1.882667775  0.36963750  1.994528135  1.165141244  1.073935784
##  [728,]  0.339965665  2.07865709  0.462816827  0.558906039  0.120804075
##  [729,]  1.739123115  1.03705984  3.509975046  1.302000268  0.889436032
##  [730,]  0.602036150  0.86704300  1.930543895  0.267933920  0.534806042
##  [731,]  0.607102855  1.09885437  0.574323176  0.166281312  1.240570384
##  [732,]  0.351765535  0.80064255  2.593969276  1.950517240  0.422985992
##  [733,]  3.532118167  1.41666295  0.869253479  1.562126954  2.046774021
##  [734,]  0.483978004  0.67238720  0.411577639  0.403348591  1.024212456
##  [735,]  0.588420433  2.09609303  0.472919168  2.212740289  0.896722703
##  [736,]  0.481746644  2.83107470  0.241615396  0.702702702  3.692074024
##  [737,]  0.792066813  0.87030600  0.663418621  0.225510648  0.332150615
##  [738,]  0.612090894  0.85738358  0.953086711  0.940456983  0.539530661
##  [739,]  1.250072005  1.20502491  0.933707617  0.513141753  0.916553365
##  [740,]  0.864320089  0.71654880  0.921860970  0.409886847  0.569251927
##  [741,]  2.640382931  0.91147867  0.780553105  0.271603839  1.322062201
##  [742,]  0.746576453  0.56758147  0.679453381  0.304170769  1.139853445
##  [743,]  0.618065877  0.74703550  1.035288891  0.179453960  0.605040682
##  [744,]  0.271730980  1.96250194  1.560847098  1.627936220  0.580769784
##  [745,]  0.101953989  1.04152189  1.429054698  0.776898761  0.737201155
##  [746,]  0.907189549  1.02462706  0.733733852  0.784646852  1.421522817
##  [747,]  1.672161636  0.63956334 -0.020746280  1.632956117  1.786667377
##  [748,]  0.238226556 -0.13869107  0.783051650  1.016556708  0.445616035
##  [749,]  1.695873543  2.55327080  1.838124675  2.523159481  1.224581538
##  [750,]  1.002617660  0.10175099  1.273718125  0.181369127  0.915780115
##  [751,]  1.012873442  1.33606424  0.854231135  0.659895234  0.395471559
##  [752,]  1.245235025 -0.11190522  0.803154098  0.357873867  0.732647432
##  [753,]  1.338993224  1.19338210  1.126724039  0.757348466  0.669834030
##  [754,]  0.966987988  0.10943385  0.691315686  0.773267736  0.873135590
##  [755,]  1.814301774  1.24816993  2.136249403  0.253503275  0.818974179
##  [756,]  0.927982974  0.44472607  0.882713626  7.330711943  1.947146005
##  [757,]  2.068536786  0.24416321  0.921788828  0.635792796  0.265582075
##  [758,]  1.067087510  2.58151534  0.385283848  0.943816074  1.028287724
##  [759,]  2.595017193  1.34832993  4.399182745  0.673196791  0.523901367
##  [760,]  0.778297739  2.66130916  0.697676267  1.364234690  0.508938304
##  [761,]  0.597621557  1.55776059  1.570661036  1.319556533  0.947798429
##  [762,]  1.567685166  0.89132261  1.897463656  0.300541553  1.026156058
##  [763,]  0.299659361  0.40156404  0.978854204  0.278412301  1.673995874
##  [764,]  4.133339840  0.78969798  0.835348567  0.209613491  1.289331089
##  [765,]  1.050478226  2.23790709  1.684848030  0.071900220  2.436481946
##  [766,]  1.385813853  1.07977759  0.611483654  3.083501433  2.328377709
##  [767,]  2.690461699  0.04843554  0.268483022  1.094902553  0.822744895
##  [768,]  1.201484831  1.02920863  1.117733589  1.569706966  0.226330858
##  [769,]  1.795180099  0.65740189  0.596783184  0.975937492  1.333599540
##  [770,]  0.477459063  0.33651697  0.448210382  0.978668351  0.125822191
##  [771,]  1.290066889  1.38176858  0.730018317  2.166495320  0.782786299
##  [772,]  1.748604705  0.39696042  3.327266357  0.824665299  1.997830846
##  [773,]  0.747001529  1.40363008  0.722514668  0.698701295  1.052312418
##  [774,]  2.985346599  1.11378468  1.813800251  1.099611145  1.031435010
##  [775,]  1.373516503  1.53373901  0.286668274  1.128769766  1.053414624
##  [776,]  0.824528584  0.40332910  0.369662958  0.818036001  1.310636550
##  [777,]  2.381144533  0.91792415  0.515503350  1.508025619  3.151075736
##  [778,]  0.214226084  1.38696214  1.858893825  0.223158492  0.712578205
##  [779,]  2.434180250  1.18265224  0.899519187  0.695157252  0.574366453
##  [780,]  0.997519117  0.67839918  0.850782039  1.874167978  1.082807996
##  [781,]  1.605616836  2.84109884  1.793079091  0.657073799  0.171060022
##  [782,]  0.003087245 -0.03882673  1.712268475  0.542066299  0.664398615
##  [783,]  0.217617027  0.87521814  0.938880088  1.062497010  3.108101407
##  [784,]  0.827653273  0.67994696  2.516854509  0.369910253  0.122499043
##  [785,]  1.354349747  0.32143726  0.462162379  0.670151190  1.333853675
##  [786,]  1.740246453  1.27236417  0.428921900  0.329650814  0.035636688
##  [787,]  0.353938572  2.08105792  2.274067927  1.664354623  1.384873427
##  [788,]  1.098592356  1.68917665  0.818476929 -0.041914684  3.470524396
##  [789,]  0.982805278  1.66855388  1.902854805  0.979434192  0.986932926
##  [790,]  0.713588558  0.78372814  2.608600070  2.371746399  1.054863849
##  [791,]  1.512940711  1.51584496  0.918657578  0.370407118  0.422693347
##  [792,]  0.102760091  0.54840320  1.048376039  1.053029201  0.412864596
##  [793,]  1.641285961  2.53845688  2.413415352  0.812513662  2.471918813
##  [794,]  1.060168497  1.05978418  1.049224323  2.319273926  0.731915653
##  [795,]  1.549172254  0.61389441  0.518023970  0.761995268  0.511151395
##  [796,]  0.426484408  0.12960984  0.513285484  1.304177584  0.956595497
##  [797,]  0.777161132  1.45020696  0.829718855  1.869583185  1.356129769
##  [798,]  0.852710113  1.44954884  0.374429426  0.371619829  0.787249526
##  [799,]  1.913886659  1.55691094  0.419029143  0.684050967  0.261784833
##  [800,]  0.544033534  0.28863506  1.212961264  0.123216409  0.732752266
##  [801,]  0.529891812  0.59221245  1.416085015  0.630979672  0.141334617
##  [802,]  0.282537293  1.22673157  0.388990721  0.392346797  0.359950679
##  [803,]  0.815593843  0.29604963  0.717660461  2.013351628  0.414440018
##  [804,]  0.986738857  0.59178965  1.543405121  0.624068922  1.482273313
##  [805,]  0.596836736 -0.05855630  0.786186152  1.136330417  0.645522402
##  [806,]  0.740131001  1.58146229  4.428196992  1.261769412  0.067922198
##  [807,]  0.574620800  1.16207387  0.438608348  1.873000173  1.389969630
##  [808,]  1.084637221  1.11186597  1.035613830  0.581467482  1.266469513
##  [809,]  0.392142496  1.11828805  0.973480289  3.498485153  1.275822404
##  [810,]  0.841749830  0.81270801  1.519815507  0.905314387  2.490507361
##  [811,]  1.373136857  1.29286179  0.422466447  0.686731559  0.817372227
##  [812,]  0.410453774  0.63358619  2.062289668  0.673714218  1.389962468
##  [813,]  0.668434387  0.86226455  1.473527908  1.088361653  1.088242907
##  [814,]  0.570437686  0.42854133  1.198624830  0.749601692  1.384205583
##  [815,]  0.778674564  0.67799712  0.714192440  0.286863647  1.526808605
##  [816,]  1.090827663  0.86477781  1.199549975  1.914897264  0.667484877
##  [817,]  2.343855629  0.27861072  0.836294306  0.104548111 -0.160305034
##  [818,]  0.705585206  1.20912484  0.890636484  0.328077574  0.409242989
##  [819,]  2.597640564  0.52921088  1.380661857  0.795355575  2.977581117
##  [820,]  1.404349751  0.42526267  0.030512504  0.195728350  0.494008108
##  [821,]  1.020505753  0.39097027  0.698282571  2.850514275  1.260015126
##  [822,]  0.998105882  0.29840993  0.684227899  0.935776751  1.428236473
##  [823,]  1.435311562  1.30804052  0.315019475  0.489566742  1.767145888
##  [824,]  0.804863989  0.94540292  0.401715737  0.775450218  0.384896252
##  [825,]  0.089784737  0.07985661  0.315155817  0.092275141  1.059485056
##  [826,]  0.561262231  2.14504834  1.330027854  0.804745123  0.380432769
##  [827,]  1.096025337  0.61096240  1.737625053  1.270091282  2.529142599
##  [828,]  0.671327276  0.53652163  0.541775046  0.571918731  2.336879525
##  [829,]  0.216071414  2.27501257  0.557270491  0.866397915  2.313220402
##  [830,]  0.923622375  0.90887819  0.710491247  1.695747030  2.038288106
##  [831,]  0.341464335  1.01277669  0.422886691  0.395712596  1.286769299
##  [832,]  1.310938229  1.33327898  1.414750215  1.176503948  1.180495561
##  [833,]  0.735468686  0.59200260  2.116506208  0.575876273  0.877535320
##  [834,]  0.387948328  0.40573160  1.542318669  0.351209697  1.793844742
##  [835,]  3.572905204  0.95205686  1.714822062  0.906491497  1.374775543
##  [836,]  0.875045457  0.64071207  0.127623971  0.458444334  1.655211667
##  [837,]  1.153670700  2.65338576 -0.032683605  1.541255947  0.609631953
##  [838,]  1.718169034  0.57839409  1.413906964  1.525694514  1.204825451
##  [839,]  0.537833419  0.66414201  1.257548997  0.533170762  1.484126604
##  [840,]  1.094558177  0.13722713  1.512147662  0.556855434  0.667937329
##  [841,]  0.670443466  0.97981199  1.394087605  0.633749283  0.305393757
##  [842,]  0.094851778  1.52503558  1.565255501  0.883836847  0.662169217
##  [843,]  0.432375226  0.94821160  0.383797735  0.676735137  0.243368014
##  [844,]  0.746830796  0.73629961  0.370613057  0.522827578  0.810516778
##  [845,]  1.113550287  1.59064361 -0.005159785  0.404701116  0.457293668
##  [846,]  0.614652705  0.61452920  2.280226168  1.321284338  0.615674502
##  [847,]  0.660814928  0.55778433  2.228417330  2.343184194  0.261162012
##  [848,]  0.866458246  1.53913935  0.411740035  1.598768866  0.615788341
##  [849,]  0.301360190  0.54310610  0.567102450  2.701159161  0.131862756
##  [850,]  1.648215256  0.44210046  0.356895116  2.598212047  1.126145638
##  [851,]  2.784001227  0.90555051  1.300561070  1.320442328  0.945996529
##  [852,]  2.994568864  0.71498729  1.517256082  0.355316591  0.956224892
##  [853,]  0.854304145  1.14370505  0.170368530  1.104205211  5.254475124
##  [854,]  0.629678123  0.38149058  0.995182824  0.348446520  0.717515422
##  [855,]  0.794874975  1.73895770  1.829025488  0.356979103  1.761897039
##  [856,]  0.852826076  1.27146588  1.054693455  1.075148353  0.140110167
##  [857,]  1.353713942  0.90805468  0.614923240  0.465934189  0.401392462
##  [858,]  0.234338040  0.12148533  1.139730295  0.671489765  1.445378460
##  [859,]  0.477926752  0.95711475  0.673333357  1.443568785  1.573034130
##  [860,]  0.219203157  2.16570996  1.109541687  0.941469406  1.334038803
##  [861,]  0.849564899  0.28920972  0.480961815  0.379915163  1.057720493
##  [862,]  0.314140497  0.83422798  0.527398481  0.964199659  1.032782670
##  [863,]  0.593915734  2.60721615  1.211372284  0.374729775  2.554342687
##  [864,]  0.799083490  0.27666549  0.757823530  0.443575573  0.831703363
##  [865,]  0.575920308  1.07677265  1.345396719  0.818700454  0.352859544
##  [866,]  1.120764042  1.76182047  0.702306404  1.275615754  0.971580886
##  [867,]  0.468117538  0.55608146  0.768765569  1.109150550  0.529343523
##  [868,]  0.209425851  0.99283533  0.644384840  1.404687079  0.632532480
##  [869,]  0.865815685  1.37305072  1.071883613  0.683869423  0.399630520
##  [870,]  1.000921843  0.45176582  1.364381216  1.990061788  1.780806800
##  [871,]  0.872669546  1.00980864  0.423130281  0.571982943  2.525495562
##  [872,]  0.731241250  0.73148215  0.115214251  1.965184509  0.651041306
##  [873,]  0.113688256  0.64036347  0.990347679  0.097827406  0.714494922
##  [874,]  1.257973816  0.81528619  0.858581640  0.331043381  1.003313233
##  [875,]  2.928893193  0.91315868  2.071547333  1.408693625  1.285672528
##  [876,]  1.105932495  1.62373062  0.221928507  0.049335057  0.570854785
##  [877,]  0.284845216  0.54055834  0.563336750  1.048592876  0.118916661
##  [878,]  2.203796612  0.47655511  0.703748780  0.734023628  1.011228819
##  [879,]  0.685201588  0.60667668  0.838119095 -0.092018075  1.285390989
##  [880,]  0.968603533  0.92888087  1.161396929  1.298144578  0.322750254
##  [881,]  1.596944961  2.67253669  1.159169793  0.537340683  1.188375215
##  [882,]  1.009110728  0.78064704  0.870663228  0.775529208  1.313060992
##  [883,]  0.571569597  0.51749909  0.364747095  0.704236264  0.465169364
##  [884,]  0.708608439  0.87778300  0.827170816  0.536850746  1.128419449
##  [885,]  1.482938929  1.52799019  1.217971016  1.918453329  0.873492830
##  [886,]  0.597916923  2.01559831  0.062661365  2.610775909  1.580862990
##  [887,]  0.099814011  0.73043586  2.101670762  0.825506182  0.780039098
##  [888,]  1.537628080  0.91220956  1.140206759  0.266645994  2.140711964
##  [889,]  0.362396028  1.06620647  2.039405981  0.099763721  1.022340395
##  [890,]  1.336064427  0.38170112  1.373819881  2.911501603  2.429484740
##  [891,]  0.951902833  1.40211995  0.711351207  0.667836870  1.191317219
##  [892,]  1.291566826  0.39202120  1.893015964  0.828039001  0.851435919
##  [893,]  0.569049532  1.00969677  0.461898591  0.292950599  0.904256801
##  [894,]  0.431820589  0.88167305  0.388804865  0.343106685  1.026529926
##  [895,]  1.072282871  0.73127833  1.702495867  0.560325258  0.914104432
##  [896,]  2.284125404  0.34408636  0.554425826  0.301506636  2.845077302
##  [897,]  1.642813289  0.51288556  0.436842501  0.857804597  1.256108816
##  [898,]  1.587035676  1.03364459  1.662110807  1.043749599  0.758782156
##  [899,]  1.255918463  2.22444847  0.388208014  0.429865240  0.619854987
##  [900,]  0.975218767  0.41131925  0.621987589  3.751067372  0.125183521
##  [901,]  1.066847271  0.58531522  1.595491405  0.283454320  0.753379408
##  [902,]  0.207717280  1.90042140  0.601898734  0.215719126  0.722369865
##  [903,]  0.500672049  1.55580752  1.204429235  0.569977857  1.464816698
##  [904,]  1.088316167  0.72367426  0.742883671  1.135128212  0.591066538
##  [905,]  1.496607180  0.85727866  1.108797477  0.955152407 -0.043711163
##  [906,]  0.836579835  0.40471407  0.212855953  1.344389487  0.776601009
##  [907,]  1.362615019  0.38628815  0.460843202  0.745102245 -0.151662972
##  [908,]  0.532748118  0.32428521  0.360724895  2.008139463  0.825463695
##  [909,]  1.565203376  0.04177778  1.079186271  0.987773796  1.101610920
##  [910,]  1.017734247  0.99705417  0.976380685  0.630216398  0.597727318
##  [911,]  1.406236122  0.61456201  0.768308707  1.099143615  0.261766120
##  [912,]  0.629623700  0.58331125  1.719055451  0.119830505  1.088475654
##  [913,]  3.122902428  0.69830358  2.189113919  0.163095264  0.215101617
##  [914,]  0.623936911  0.35867109  1.179615314  0.591581143  0.676645527
##  [915,]  0.657230513  0.36384916  0.608779549  1.666852626  2.698677829
##  [916,]  0.332654655  0.99892829  0.333390331  0.729462185  1.800404103
##  [917,]  0.659629319  1.68515489  2.747916592  0.607511039  0.486272068
##  [918,]  1.302338395  0.55979605  0.734156436  0.661607067  1.158521354
##  [919,]  0.407288648  0.49075281  2.240654524  0.355502620  0.905538371
##  [920,]  0.730749958  0.17843986  1.540015794  1.058816958  0.189874465
##  [921,]  0.451523010  0.66845880  0.239623596  1.385641816  1.132252053
##  [922,]  0.932583701  1.86785505  1.530694787  0.833213975  1.587447960
##  [923,]  0.559432963  0.87339123  1.823080908  0.505188224  2.675397761
##  [924,]  0.629623719  1.28876053  0.301192008  0.467585612  0.885518284
##  [925,]  1.765435120  2.00874466  0.250472518  0.591001805  1.743453645
##  [926,]  0.614695450  1.38716688  0.861795909  1.056862829  1.328827913
##  [927,]  0.519572851  0.08173334  0.876309339  0.761448105  0.627532088
##  [928,]  0.960673264  0.42696567  2.806543005  1.532970497  0.755244643
##  [929,]  0.972781688  1.64562999  1.023864898  0.276603903  0.586343583
##  [930,]  0.451886637  1.01308150  0.501732962  0.042852181 -0.100596628
##  [931,]  0.770476701  0.40779459  0.394561014  0.118675595  1.184084533
##  [932,]  0.624846245  0.23103413  1.736927801  0.907218205  1.446688821
##  [933,]  1.495293241  1.42305108  1.173540566  0.581500556  0.452491246
##  [934,]  0.090253901  0.23887959  0.574216011  0.446908361  0.550221210
##  [935,]  0.424861946  3.32563182  0.194789102  1.327006664  0.895597169
##  [936,]  0.459652679  2.19815826  1.013724540  0.747380150  0.609249444
##  [937,]  0.791408731  1.63982825  0.662208798  1.177682276  0.011343012
##  [938,]  1.036029557  1.70766016  0.438662319  1.437490016  0.534721298
##  [939,]  1.054880627  1.79884672  0.599861888  1.005308012  0.557253065
##  [940,]  1.310199378  1.05215100  1.436075664  0.717633287  1.726839177
##  [941,]  1.642602175  1.58794824  2.932367344  4.498444257  1.533527430
##  [942,]  0.382561103  1.46205679  0.802717854  2.179375257  0.754579022
##  [943,]  0.653525895  0.51574072  1.140456424  0.630210794  0.518770823
##  [944,]  0.530553885  0.86199579  0.389212428  1.726429494  0.918853595
##  [945,]  0.576237192  2.02414444  1.596299623  0.327111460  1.200289712
##  [946,]  0.205695244  0.21718018  3.385019332  1.639031531  0.501529767
##  [947,]  2.259921900  0.15492220  0.878015009  1.469627720  0.964893982
##  [948,]  0.775791543  3.18453455  0.587925166  1.473716488  0.699103403
##  [949,]  0.860134152  1.46535699  2.654447075  1.351866078 -0.028939365
##  [950,]  0.511157285  0.62823945  1.305003945  0.390423012  0.716976052
##  [951,]  2.046573155  1.33405753  2.031368161  0.431083147  0.409373939
##  [952,]  0.327377526  2.04139676  0.738184626  1.080249306  1.481772407
##  [953,]  0.638650617  1.68507589  0.939892312  0.515962221  0.699472673
##  [954,]  1.266577524  1.62332160  2.684622294  0.794093824  0.422117441
##  [955,]  0.491201246  0.29131395  1.009218891  1.516995908  2.431621811
##  [956,]  2.090717845  0.25934582  0.711779749  0.588275277  1.313538141
##  [957,]  1.513217367  0.33866938  0.569824892  1.557494622  1.021421277
##  [958,]  1.603262619  0.45739163  0.272859303  0.413232434  1.167958975
##  [959,]  1.128553210  1.12642713  1.143990165  0.711875858  0.978403374
##  [960,]  1.038836354  1.10303464  0.342630508  0.485644396  0.657733312
##  [961,]  0.964829991  0.37572165  2.155779852  2.839261953  1.110420114
##  [962,]  1.325158455  0.56515923  1.088133985  1.132120209  0.838964890
##  [963,]  1.756835117  1.32291676  1.760953526  0.764737939  0.736553065
##  [964,]  0.492563294  0.28780880  1.213786697  0.933561170  0.755101891
##  [965,]  0.141069927  0.53938032  1.048586806  1.010028419  0.418529984
##  [966,]  0.283736023  0.68389335  1.196338234  1.571296631  0.578449310
##  [967,]  0.268561513  2.61921880  2.348472422  1.861511264  0.746261278
##  [968,]  0.311086037  0.28434188  1.626682464  1.133144101  0.403410967
##  [969,]  3.544811122  0.72859988  1.153088606  1.648864116  1.175116768
##  [970,]  0.550478837  1.71789520  4.943255072  0.352089799  1.581792496
##  [971,]  0.919982738  0.33862766  2.839064869  0.299926338  1.324365146
##  [972,]  0.257779861  0.41905212  1.533004195  0.867705857  0.618340077
##  [973,]  0.994578150  0.58446264  0.602277601  1.987986134  1.392868594
##  [974,]  0.672890242  0.35750938  0.410663635  1.317771188  0.447260103
##  [975,]  0.346051427  0.53272318  0.590831603  1.340155139  1.814905227
##  [976,]  0.951526793  0.75937346  0.661817448  0.392805273  1.372669996
##  [977,]  0.525957338  2.34111753  1.007391425  2.270392958  0.193032985
##  [978,]  0.316050283  1.25150053  1.237339741  1.744935741  1.955132893
##  [979,]  2.539179490  0.41719193  1.231413683  0.583497515  0.999261672
##  [980,]  0.724064686  0.33670288  1.963008202  0.868723059  0.809254893
##  [981,]  3.764252412  1.82097823  0.581749888  2.902979409  0.505457033
##  [982,]  1.388647703  0.81507355  2.810544246  0.821095867  0.432027724
##  [983,]  1.784383638  0.84984567  0.789079621  0.167252117  0.870100106
##  [984,]  1.082123725  0.81085931  0.641645049  1.268490939  1.361092594
##  [985,]  0.375006319  1.28734995  1.938571442  1.664104490  0.825939968
##  [986,]  0.565371655  1.30532857  0.339724855  1.999637474  0.080867188
##  [987,]  0.397750832  0.90860848  0.613859304  1.001410059  0.905608775
##  [988,]  0.422981973  1.01728566  0.745258737  1.109536966  0.624599651
##  [989,]  0.656143795  0.87928841  2.306890045  0.068022294  1.431627043
##  [990,]  0.722769461  0.33152798  0.251075991  0.901515373  0.913776133
##  [991,]  0.989496853  1.73438286  0.907499160  1.077571419  0.071145035
##  [992,]  1.651142177  0.40656608  0.688983985  1.572629979  3.066389481
##  [993,]  0.173050450  2.28301840  0.937685215  1.870220113  1.908107823
##  [994,]  0.460463231  1.25765649  1.687404177  0.476983446  0.332344611
##  [995,]  0.885207685  0.83992695  0.501572569  0.791465302  3.868609403
##  [996,]  1.674726524  1.45164073  1.328518422  0.587442561  1.695365896
##  [997,]  0.531715602  2.15764923  1.293452693  0.232637419  1.416551700
##  [998,]  1.276183113  0.76741073  1.024740052  0.944790230  2.400968932
##  [999,]  2.349745959  1.45612920  0.459839940  1.165741111  2.547309737
##                  [,6]         [,7]         [,8]         [,9]        [,10]
##    [1,]  1.2899374354  1.110680080  0.834448773  2.420180096  0.486254152
##    [2,]  1.7519148312  0.837430880  0.668649990  1.842591155  0.804615795
##    [3,]  0.5795004839  0.906067682  1.189284825  1.731635106  0.945028980
##    [4,]  1.6969010557  0.042511599  0.514824063  0.771979696  0.373896923
##    [5,]  2.0946580913  1.891896348  0.575030791  1.284653244  1.064441707
##    [6,]  0.8171043767  0.094350576  1.577370783  1.871690809  0.458895046
##    [7,]  0.3772002752  1.155763935  1.205151729  0.857267269  1.907720833
##    [8,]  1.8586670525  0.058170576  0.951193361  0.488550856  2.635210676
##    [9,]  0.7941454520  0.703020789  1.270445451  0.088489660  1.961500500
##   [10,]  1.4067216273  0.812226461  0.318481367  1.060883152  2.658623123
##   [11,]  0.8430285354  1.342575380  0.910045983  0.487646107  1.781064152
##   [12,]  0.1134291108  0.536572397  0.756955149  1.291929251  0.122383413
##   [13,]  0.4055054555  0.868967100  1.019356908  1.033962828  0.983386867
##   [14,]  0.6251423434  1.422528523  0.531960091  0.170615403  1.403151589
##   [15,]  0.8882987383  1.258673699  1.326308802  0.882005273 -0.099912507
##   [16,]  0.7994052297  1.758529973  0.191689349  1.207225383  0.991251453
##   [17,]  1.1257633108  0.116870239  0.571725730  1.156145507  0.225330450
##   [18,]  1.2016589850  1.085061672  0.459641715  0.414608491  1.008758057
##   [19,]  0.6070016183  0.911290097  0.437972622  0.465274977  0.361388749
##   [20,]  0.8494472236  1.333096763  2.504333340  3.739759290  3.278909000
##   [21,]  1.3381630009 -0.083409092  1.711746547  1.335965374  1.083170780
##   [22,]  0.6702440701  1.112175047  2.594584032  0.217691753  0.623114021
##   [23,]  1.6610204808  2.025616672  5.566927521  0.479806935  1.569939820
##   [24,]  0.3549737492  0.841888189  0.643986730  0.316878187  0.965971668
##   [25,]  0.6607506977  0.549977493  1.175477407  1.958327627  1.306972123
##   [26,]  0.5184947474  0.494570098  1.206337372  0.701692337  1.390914947
##   [27,]  0.6622726936  1.899077491  0.456554990  0.495214394  3.234434313
##   [28,]  0.9903859173  0.631601899  0.444834611  1.772612813  1.220537329
##   [29,]  1.4934681789  1.441724429  0.963189338  0.837712883  1.216782829
##   [30,]  0.6677236788  1.230602671  0.161915057  0.691540989  0.631618131
##   [31,]  1.0140643066  0.635922462  0.686249013  1.177259740  1.007673608
##   [32,]  1.7326956621  1.710797413  0.535474601  0.740854421  0.590681473
##   [33,]  1.3176973778  2.747081380  1.596831106  3.558460005  1.549918823
##   [34,]  2.0471937044  0.034798863  0.173087010  0.552740028  1.337455527
##   [35,]  0.7601309046  0.522784300  0.747425625  1.032482159  1.016286925
##   [36,]  0.2803327767  0.259435737  0.322966153  0.245117888  0.649592214
##   [37,]  0.6701072888  2.396611268  0.889770377  0.485637026  0.149578105
##   [38,]  0.3582263764  0.744750504  0.582856094  0.939628937  0.488296374
##   [39,]  1.2024975485 -0.075405859  0.613381554  0.365565443  0.456439212
##   [40,]  0.3491275184  0.552465298  1.097898123  0.259500046  0.740530249
##   [41,]  1.2368918817  1.025432582  1.217526189  0.761844301  1.401425562
##   [42,]  0.6750073382  0.214351386  1.064086100  0.513690565  3.621987871
##   [43,]  0.9323030619  1.703277141  0.856068972  1.728089718  0.390558830
##   [44,]  1.8280025092  2.535981951  1.883098236  0.784416599  0.880680606
##   [45,]  1.3664114274  0.743700092  0.596078613  1.054401703  1.488331073
##   [46,]  0.2762484156  0.499605535  1.077154763  1.065108163  0.508531740
##   [47,]  0.5882980087  1.201338795  3.240491912  3.548075441  1.364339379
##   [48,]  0.5766378930  0.068167663  1.621579896  0.706750654  0.508787764
##   [49,]  1.5052214239  1.734575020  0.236673281  1.555114756  0.264297528
##   [50,]  2.6193476305  0.808445958  0.462143885  0.559223215  0.496893013
##   [51,]  1.2509058170  1.516204623  2.638859172  0.033982725  0.464779648
##   [52,]  1.5478745529  1.812692939  0.568502390  0.910904568  0.857286625
##   [53,]  0.8574158285  0.597437197  0.664199090  0.116157266  1.068281244
##   [54,]  0.9390979832  0.247961224  0.527329020  3.719837960  1.157062859
##   [55,]  0.4001436872  0.459673974  1.092024833  0.212833465  0.971936197
##   [56,]  1.6391363458  0.891636084  0.918185366  0.846889352  1.218708507
##   [57,]  0.8853447491  1.146967804  1.078279245  1.119633540  0.813745610
##   [58,]  0.6124179054  0.998613441  0.586129541  0.951073833  0.086419030
##   [59,]  1.1421382506  0.535182113  1.720950390  0.958416857  1.037748371
##   [60,]  0.1655730431  0.428452651  0.600327729  0.435964346  0.969428319
##   [61,]  0.8396559490  0.673384528  0.973983385  1.830436236  1.298137559
##   [62,]  0.6333508793  2.160732400  1.572530532  0.587516043  0.563634411
##   [63,]  1.2932615690  0.104648317  0.459631065  0.688175261  0.164584446
##   [64,]  0.9238985888  0.128999301  0.611639216  0.526998602  0.699790895
##   [65,]  1.6129244997  2.141067134  1.087373048  1.013894524  0.921898475
##   [66,]  0.8342504188  1.535698524  0.433465689  1.349306349  0.603117757
##   [67,]  0.8648393098  0.467685837  2.642784860  0.330962711  1.209550780
##   [68,]  0.1359920476  1.452554812  0.576256187  2.259354742  0.338321803
##   [69,]  1.5789120760  0.363894719  0.664776615  1.587019495  0.176701409
##   [70,]  1.4046560619  0.780723871  1.378369167  0.967406498  0.942137490
##   [71,]  1.0114743375  1.269651964  1.992671155  0.566512804  0.673512782
##   [72,]  2.0395195023  3.629689742 -0.010874370  0.345077553  0.689699950
##   [73,]  0.7058718272  0.686719683  0.631464765  2.880304764  0.345229834
##   [74,]  1.4442372303  0.591697814  1.334463669  0.138101491  0.912937526
##   [75,]  2.4277375996  0.635103549  1.401585260  1.716002650  0.672101963
##   [76,]  1.2915048614  4.182594316  2.522973096  1.663300476  1.195654635
##   [77,]  0.4730844115  0.367774949  0.310021607  0.880226894  3.225935309
##   [78,]  0.1075146630  0.486870913  1.101843189  1.903484755  0.654237898
##   [79,]  0.4524082604  1.649873574  2.372965681  2.189761833  1.365982779
##   [80,]  0.8817915448  0.284575311  0.625362382  1.852236719  1.525294916
##   [81,]  2.3482238569  0.707659206  0.742687938  1.394005358  0.772496890
##   [82,]  1.4971835562  3.878888772  0.512978583  2.368080854  0.557706855
##   [83,]  1.2384441811  0.502065466  0.149014502  0.242876383  0.930654817
##   [84,]  1.8293274088  0.790284770  3.138689536  2.297225116  0.310566047
##   [85,]  1.0128492706  1.129328804  0.902438146  0.328827840  2.555985278
##   [86,]  1.3137537584  0.027410501  1.085673747  0.687516006  2.685516999
##   [87,]  2.5749451639  0.305423852  0.486318212  3.099697641  0.354420089
##   [88,]  1.4646303384  0.974236430  0.653424628  1.815188263  0.666291037
##   [89,]  0.8366107910  0.706554580  0.162285916  1.784191536  1.449980309
##   [90,]  1.6307425513  0.279336042  0.731331146  0.624051552  0.651623673
##   [91,]  0.5772803756  1.174733949  0.399019522  2.644416034  1.076348217
##   [92,]  0.5452894711  0.397119285  1.428998724  1.861647466  1.667814935
##   [93,]  1.3780438305  0.061866287  0.433698934  0.296970537  0.706969013
##   [94,]  0.6300800658  1.646306316  0.105514583  0.957926243  0.904627644
##   [95,]  0.9784188744  1.350294565  0.370905050  0.439185930  1.456997247
##   [96,]  0.2717757743  1.045030621  0.396354783  1.762063887  2.470084870
##   [97,]  0.8922674521  0.938926928  2.358187543  0.702458918  2.817961380
##   [98,]  1.1160198170  2.512030614  0.394430830  2.251027970  0.575886532
##   [99,]  0.1147131668  0.911624944  1.291116719  1.102303974  0.861737758
##  [100,]  1.8400434954  2.095125515  1.247356625  1.923152191  3.296380422
##  [101,]  0.9846880661  0.783902853  1.074132599  2.443217737  1.160031148
##  [102,]  0.8827426948  0.582459029  0.883437793  0.488868546  0.583213921
##  [103,]  0.8672800116  0.965916037  0.801115105  1.311108345  0.640143079
##  [104,]  0.3190067048  0.780490258  1.717710475  1.064179326  0.489531911
##  [105,]  0.7251397407  0.447924152  0.986199850  0.436352447  0.921247261
##  [106,]  0.5806881234  1.142227811  3.771143571  1.152646101  1.220034568
##  [107,]  2.0644509639  1.405345561  1.881435265  0.504682325  0.575455952
##  [108,] -0.0402843353  1.187797640  0.993609246  0.506902985  0.008039364
##  [109,]  0.2160773269  1.337248016  0.962600041  0.134226954  1.149338396
##  [110,]  0.9237874829  0.585970405  3.328282469  2.741670560  1.028780605
##  [111,]  0.9187134762  0.839154448  2.278308433  0.759340222  1.486186563
##  [112,]  0.0460711920  2.939880887  1.159513507  1.842595353  0.323034705
##  [113,]  1.2421973572  2.354521404 -0.048067004  1.144824707  1.098419381
##  [114,]  0.6054808918  0.891155707  1.288550494  0.490997121  1.092687367
##  [115,]  0.7309865386  1.348722603  0.686605253  1.398845368  1.436348843
##  [116,]  0.0891736519  0.453298400  1.018070212  1.929091674  0.701928415
##  [117,]  1.1720367208  0.735625548  1.567095080  0.803183094  0.418338413
##  [118,]  0.2382185629  0.379595776  0.678157757  0.423108898  0.378625612
##  [119,]  0.9798760407  0.666080046  0.402803565  0.851064438  0.846750655
##  [120,]  0.2381151210  0.702285585  2.145386637  1.124528236  0.416030780
##  [121,]  0.4259525615  0.409159614  0.020751799  0.703166513  0.673994512
##  [122,]  1.5594843470  0.294134180  0.328881450  1.138640700  0.910240755
##  [123,]  1.8263198422  1.459103317  1.140357313 -0.035296882  0.981652122
##  [124,]  2.3169219595  0.173211579  0.945732338  0.293115204  0.026970174
##  [125,]  0.6804809326  1.463215407  1.310357355  0.922336880  1.421155031
##  [126,]  1.1439984353  0.568307589  0.297918827  0.850141674  1.058046205
##  [127,]  3.1544694617  1.688842785  1.982077772  0.822473457  1.418840566
##  [128,]  2.8499647419  1.692617898  1.193786989  2.564342104  1.054398433
##  [129,]  0.2892241141  0.911337152  3.498051657  1.105338832  0.218408941
##  [130,]  0.3863355635  0.860789352  0.326199208  0.607229641  0.636123387
##  [131,]  1.0134769441  0.452157195  0.211683275  0.570695398  0.706107654
##  [132,]  1.1218343466  0.293653407  0.912581881  1.353631869  0.773840693
##  [133,]  0.2697791266  1.410022527  3.269433181  0.774674389  0.960590943
##  [134,]  1.0499708205  0.365828708  1.140926705  0.446438788  1.803838135
##  [135,]  0.5712051728  0.255106233  1.400145669  1.609612075  0.302871159
##  [136,]  1.0095180872  0.536755927  1.496026123  0.995813312  0.327700948
##  [137,]  0.9484442940  1.244380461  0.924715944  0.705512123  1.999749346
##  [138,]  1.2068594687  3.551392399  0.770347163  0.095713894  1.054183712
##  [139,]  1.3943255989  1.228949990  1.317070690  1.003778920  2.955971802
##  [140,]  1.0645314884  1.109702851 -0.055974311  1.485094526  0.503751544
##  [141,]  0.4861465412  0.296954956  0.635459133  0.749993850  0.779378301
##  [142,]  1.7105741876  0.184686351  0.292069462  0.623161698  2.728883409
##  [143,]  1.0005295119  0.593272196  0.583181401  0.610096026  0.758349649
##  [144,]  2.6347938218  0.168228822  1.379161469  1.573578952  0.987100397
##  [145,]  1.0156762705  1.723837996  1.040704057  1.506974073  1.964183521
##  [146,]  0.8806834092  0.949393866  1.676312715  0.489937435  0.427296050
##  [147,]  1.6843937416  1.196440129  0.940594713  0.943267894  0.497177693
##  [148,]  1.1148805375  1.982168063  0.694264325  2.194617585  1.528863191
##  [149,]  0.3336526632  0.755142154  1.361043035  0.523857991  1.256161158
##  [150,]  0.4219745757  1.860756063  1.035552260  0.340789702  0.427385549
##  [151,]  1.0489163369  0.259511131  1.725183592  1.339381780  0.849226120
##  [152,]  0.7467158121  0.833128962  2.190820416  0.417315196  1.897370160
##  [153,]  0.4431065560  0.981479862  1.271732460  0.512224519  1.030012622
##  [154,]  1.1164773827  1.143179308  1.020106164  1.087844203  1.692027481
##  [155,]  1.0956210294  0.865467253  0.173200363  1.563301797  0.178597156
##  [156,]  2.1295359537  0.187288400  1.517062538  0.914587224  1.065212428
##  [157,]  0.3995114253  2.338090072  2.168424931  0.467320869  0.867587465
##  [158,]  0.3661300345  0.715492876  0.283114693  0.201914385  0.894600927
##  [159,]  0.1759666506  1.061653901  1.054190192  2.571121490  0.521359479
##  [160,]  0.4318371095  1.890778555  1.685878296  1.068843034  0.737537023
##  [161,]  0.8809580061  0.187060784  0.597120414  0.163601107  0.076900498
##  [162,]  2.6827963215  1.065365932  0.821487530  0.385649184  0.676178837
##  [163,]  1.1377904245  0.874698214  1.043805775  0.998478416  0.603150749
##  [164,]  2.4725830424  0.926781782  1.196403553  1.287619385  1.333191680
##  [165,]  0.2239270837  0.181684542  0.264488106  1.369919766  0.666675160
##  [166,]  0.8698696020  0.772154904  1.703337670 -0.107312723  0.570370874
##  [167,]  0.2701375701  1.156437129  0.624608056  0.694222288  0.293696006
##  [168,]  1.0442070911  1.099047432  0.722311782  0.838072906 -0.017577989
##  [169,]  0.8826838242  0.842344537  0.209327320  0.326149910  0.397758979
##  [170,]  0.3576283045  2.684454124  0.784455365  0.413083660 -0.050696703
##  [171,]  1.0740373741 -0.099241522  3.144742565  0.702974078  4.700581899
##  [172,]  1.2347806926  0.356750583  0.681319908  4.227211216  0.631382061
##  [173,]  1.0096925070  0.579436573  0.260367344  1.263548908  0.633702325
##  [174,]  0.7897791962  0.642237696  0.260766307  0.818902396  1.763930987
##  [175,]  1.5271255429  0.527994046  1.845538890  1.213408885  0.107581652
##  [176,]  1.2619843410  0.500565584  0.987794559  1.816891207  0.479861867
##  [177,]  0.8192428932  1.097533333  0.957462285  0.501287252  1.018551182
##  [178,]  0.9537371359  1.084454449  0.523721236  0.225472551  0.390587988
##  [179,]  0.4719305193  0.477295378  1.546879418  1.186233903  0.068885728
##  [180,]  0.1702592166  1.301215318  0.970609800  0.656470027  0.886724736
##  [181,]  0.4519125383  0.604794979  1.080420878  1.826585158  1.041844598
##  [182,]  0.4790585162  0.934975069  1.583747982  1.006540668  1.351588511
##  [183,]  1.7393240214  0.297116750  0.642579762  1.384223709  0.306009659
##  [184,]  2.0548786588  1.071746978  1.151212522  1.068138037  0.874936285
##  [185,]  0.5763402068  0.961134657  0.772290051  2.032763585  0.408152245
##  [186,]  0.6006016710  0.810054128  0.395476485  1.814974081  0.893877719
##  [187,]  1.3169285769  1.018719043  1.715887320  1.455641634  2.363589653
##  [188,]  1.4911584644  1.226583390  0.985054439  0.350114727  0.538464478
##  [189,]  0.6579512791  2.669059396  0.276329577  0.506450285  0.132077951
##  [190,]  0.7008171392  1.137250559  1.047667741  0.369371746  0.544251181
##  [191,]  2.0794681688  1.757968325  3.336728815  1.473758117  0.551124875
##  [192,]  0.9243203661  1.765844314  0.531848891  1.179330246  0.153038161
##  [193,]  1.2027634340  2.400841178  0.620511262  0.536208388  0.683772689
##  [194,]  0.4073198174  1.300763235  0.764634944  0.784527350  0.680902373
##  [195,]  0.3915615213  1.058721102  1.684698506  1.322974697  0.202005822
##  [196,]  1.0474266197  0.146544550  0.645432364  0.388701936  0.432744336
##  [197,]  0.3187506114  2.405277247  0.838364092  0.803425790  0.208949233
##  [198,]  1.2085453758  0.595171018  0.353474777  1.148417159  1.071255885
##  [199,]  2.0557975757  0.564971054  0.937231803  0.918597033  1.196027180
##  [200,]  0.3950235087  0.401478007  0.055899908  0.980522263  2.534052892
##  [201,]  0.5495610187  0.622504526  1.007956974  0.820663619  0.153780966
##  [202,]  1.2356598735  0.342759159  0.590907937  0.916106620  0.289590296
##  [203,]  0.6805160134  0.733701271  1.307888883  0.950509832  0.702319356
##  [204,]  1.1353389129  0.452322618  0.457688969  0.008623916  2.834340103
##  [205,]  0.3331448302  0.889985954  1.030182141  0.807422832  0.818063214
##  [206,]  1.3657262390  0.834645146  0.621556321  0.828625687  2.692627372
##  [207,]  0.2924095603  0.468801359  0.464258799  1.091273520  0.423851949
##  [208,]  1.5305142713  0.209595905  2.676596801  1.128408765  0.426960776
##  [209,]  0.9505338924  2.571256991  0.759509357  2.384583470  0.979484286
##  [210,]  0.4838642988  1.450177415 -0.109445524  1.586975092  1.153056382
##  [211,]  0.9066795872  0.351556058  0.802018616  0.609827093  1.440720332
##  [212,]  1.6924730579  1.020768517  0.428860313  0.791432962  0.572995508
##  [213,]  0.4293592817  3.348335163  0.784555837  0.170851783  0.754165864
##  [214,]  1.7472613265  1.227926094  1.198246219  1.055487554  0.526458827
##  [215,]  0.7984898839  0.915301426  1.072838452  1.100271131  1.342565957
##  [216,]  1.6493518293  0.989522838  0.366537091  1.208991428  2.625511379
##  [217,]  1.4059492252  0.703807598  0.193640435  0.518599162  0.583114870
##  [218,]  0.7864750982  0.625746666  1.144451704  0.366425330  0.734559094
##  [219,]  1.5005575933  0.540271566  0.560436247 -0.008148429  0.661122571
##  [220,]  0.6458901705  1.798368728  1.514321737  2.071605089  1.888970148
##  [221,]  0.9631156216  1.172481505  0.650455694  0.846998018  0.076413641
##  [222,]  1.8330930496  0.750173305  0.904271242  1.271098524  0.907538323
##  [223,]  0.5367207944  0.646147476  1.121546983  1.054236361  0.076325670
##  [224,]  1.2499156797  0.696921419  2.221594570  1.885051771 -0.214737570
##  [225,]  0.7196457358  0.048323232  0.079998030  0.907151245  0.262953824
##  [226,]  0.7008733134  0.748559198  0.405873791  0.565832480  1.087078149
##  [227,]  2.6750626668  1.371868621  1.822380257  1.574284751  0.016156304
##  [228,]  1.5735490496  1.034074055  1.681191632  0.926789751  0.264561695
##  [229,]  0.2980251965  0.089414471  1.140139914  0.283456423  0.818812245
##  [230,]  0.5328642167  0.752403621  1.502009015  0.167171812  1.850813054
##  [231,]  1.7095383404  0.359015615  2.633054601  1.814583863  2.856192769
##  [232,]  0.1854780845  1.635254013  0.600675859  2.183134129  1.010394841
##  [233,]  1.3347919188  1.208889951  0.693267093  0.537791485  1.511160392
##  [234,]  0.7234304535  1.319749803  0.736040499  0.654829017  0.589687589
##  [235,]  0.5091390441  0.465312413  0.445399898  1.150132697  2.003318006
##  [236,]  1.1504904617  1.202003093  0.919633172  2.215164800  0.073696799
##  [237,]  0.9121215493  0.713208193  1.687265682  1.020387990  1.189666510
##  [238,]  0.1713138575  1.029485476  0.035691548  0.330008524  0.220130621
##  [239,]  0.6160277271  0.583330155  2.119269086  0.177472437  0.706964391
##  [240,]  0.5384357512  0.373416652 -0.044427747  0.250929956  1.198944910
##  [241,]  0.3912882677  0.270642459  1.800475901 -0.001607672  1.500699890
##  [242,]  1.1507135971  1.146141199  1.870844982  0.631076786  0.525359648
##  [243,]  1.8009598183  1.169130179 -0.055348998 -0.040385773  1.698604679
##  [244,]  0.3424336564  0.513964778  0.809060650  1.191930894  0.935894129
##  [245,]  2.1337103394  0.271475728  0.389190489  0.945846599  0.435085042
##  [246,]  1.6918871980  1.278665276  0.852396506  1.213249113  0.190938442
##  [247,]  0.8156890598  0.990100902  0.616594205  1.682439462  0.362603760
##  [248,]  1.3567586831  0.939584506  2.001115650  2.243364604  2.621910525
##  [249,]  0.1254557506  0.367302499  1.709683440  1.583812443  0.281476511
##  [250,]  3.3784521366  1.579124753  0.313057922  0.225306481  0.595585876
##  [251,]  0.3156363733  1.997394876  2.136945054  2.806621477  0.954847260
##  [252,]  0.7689702262  1.304733284  0.711846710  0.154646327  1.261278357
##  [253,]  1.3316978159  3.161390426  1.828764658  4.294492498  1.109755853
##  [254,]  0.8375739035  0.585568670  0.447174790  0.571883078  2.487376725
##  [255,]  0.0958267993  0.275851205  1.515070734  1.537058480  0.819672411
##  [256,]  0.8780413922  0.550805666  0.395554159  0.174121733  1.241323635
##  [257,]  0.6345098425  0.895304455  0.668522439  1.043333860  1.467847856
##  [258,]  0.6227729411  0.679947522  0.111102222  0.757234937  0.270013800
##  [259,]  2.2271501474  0.664870360  1.610974204  1.091832964  1.671407471
##  [260,]  0.5142272926  0.516460724  1.699846034  1.288238525  0.560572613
##  [261,]  0.1683993346  1.017578994  0.172242998  1.418092355  0.697430817
##  [262,]  0.8198808230  0.353616160  0.591722496  0.719653827  0.063868331
##  [263,]  0.5391924785  0.515118190  0.512424879  0.967189707  1.556121384
##  [264,]  0.4918871478  0.271023966  1.648313181  0.847136736  2.733548667
##  [265,]  1.3850815266  1.110232609  0.354725896  0.469524936  0.607125946
##  [266,]  0.7515088252  0.361587694  1.518024287  0.344571895  0.272830032
##  [267,]  0.9377076674  2.624369609  0.859022142  0.897832643  0.318246776
##  [268,]  1.4106937543  1.558593253  0.415398782  1.018109544  1.542548000
##  [269,]  0.6364107215  1.687266335  0.859013699  0.866280431  1.658947642
##  [270,]  0.7438449529  0.470044966  0.466176081  1.287039820  0.755989620
##  [271,]  0.0255593534  1.694792807  0.279323362  0.753088123  0.776775852
##  [272,]  0.2651516983  0.717165674  0.823092670  0.867776644  0.476478422
##  [273,]  0.2687744592  1.226242426  1.289867334  0.889708657  0.687458161
##  [274,]  1.2051597887  0.983871585  0.479346897  0.469389460  0.808289642
##  [275,]  1.0935004264  1.232026418  0.747236323  1.375929800  0.787527929
##  [276,]  0.7759568398  2.042467649  1.613862340  0.666881925  0.851309959
##  [277,]  0.5364302031  1.185496024  0.134640305  0.611243759  0.657427700
##  [278,]  0.3840993413  0.539746454  1.137658930  0.779149006  0.262564026
##  [279,]  0.9552639775  2.717841663  1.306228363  1.350552791  2.685099267
##  [280,]  1.2984762664  0.529802436  1.267485568  0.984321851  0.466749549
##  [281,]  0.8288417692  1.480535041  0.650300110  0.269836777  0.588245297
##  [282,] -0.1086406967  0.236109544  1.798235197  0.739142668  1.017674943
##  [283,]  0.3093207651  0.643080405  0.622001924  1.925047627  2.204666379
##  [284,]  0.2484656730  1.155094814  1.143263204  1.277922356  0.251658269
##  [285,]  1.1498637497  0.094632361  0.484186549  1.849217073  0.434834919
##  [286,]  1.2516279484  0.819039697  0.373704046  0.778987450  1.812994566
##  [287,]  0.8286894731  0.952613972  0.816080322  1.420927786  0.702295522
##  [288,]  0.3735351710  0.850324380  0.496897885  1.282253529  1.027780854
##  [289,]  0.2645403564  0.753450368  1.379691628  3.210417146  1.050882639
##  [290,]  1.2080041865  1.320776218  0.326174216  1.513802841  1.183922175
##  [291,]  0.3377529109  1.333582758  1.005889982  0.374342448  0.683050593
##  [292,]  1.1767499255  2.695998574  0.572023137  1.087799145  0.955258367
##  [293,]  0.5961039781  0.661755738  0.508090460  4.076338703  0.248103718
##  [294,]  0.1803671263  0.396763454  1.240106355  0.507693814  0.658485613
##  [295,]  1.4809880452  0.367189671  0.281220372  0.962963241  2.855186751
##  [296,]  0.6910787956  1.800534069  0.777172385  0.762576135  1.265347665
##  [297,]  0.4096251085  1.587190853  1.039524706  2.730623139  1.346168868
##  [298,]  1.8653158777  1.604864118  1.792684718  1.236084413  0.527060694
##  [299,]  0.5753310482  0.231733316  0.295063271  1.744298898  2.216494184
##  [300,]  1.8535094759  0.697235397  1.108531576  1.453174431  0.708405288
##  [301,]  0.6245912709  1.232926766  1.920173437  2.325153524  0.755672630
##  [302,]  0.7393853537  1.098662274  3.122387646  1.692097465  1.015057466
##  [303,]  0.9749102724  0.863789613  1.117275433  0.920909569  1.633814125
##  [304,]  0.1642250850  0.398728523  0.639463685  0.932288348  3.077852807
##  [305,]  0.7152668360  0.797926215  0.368670113  1.720097043  0.732027372
##  [306,]  1.1861586872  1.776011345  1.160979736  1.842411754  0.146617254
##  [307,]  0.1319970485  3.183266910  0.853526421  1.383481218  1.739820255
##  [308,]  0.0636293061  0.800773079  0.613298314  1.386620886  0.959072392
##  [309,]  1.0861914336  0.977786156  1.365373250  1.135667495  1.443979445
##  [310,]  2.3720142850  0.078313690  0.407992117  0.932189218  0.671955283
##  [311,]  1.1637038768  0.647418557  0.306196810  0.890461385  0.792465587
##  [312,]  1.6199880276  0.519679206  0.853424252  0.563518816  0.745307047
##  [313,]  0.6095614043  1.083321285  0.216598157  0.892009040  1.253995841
##  [314,]  0.1631993092  0.746814890  1.416464212  0.631563460 -0.063610510
##  [315,]  1.1078478533  1.772268312  0.448204150  0.362042527  1.754901894
##  [316,]  0.7246197089  0.165514265  0.734781434  1.431159502  0.465097916
##  [317,]  0.4755240178  0.255437188  0.928079902  0.226124125  0.212904619
##  [318,]  0.8239340763  0.476172540  0.837991146  0.823748954  0.285070380
##  [319,]  0.9220472957  0.830790382  1.496375491  0.739543456  0.414678691
##  [320,]  0.6769872330  0.627651041  0.054128437  0.058235327  0.077536380
##  [321,]  0.8277335220  1.326108814  0.735942920  0.634850012  0.051567133
##  [322,]  0.1663029451  0.352712989  0.749095865  0.825003864  0.421780959
##  [323,]  0.8223329172  0.805942850  0.568683537  2.955569010  1.420853882
##  [324,]  1.0130645425  1.916119521  1.663892941  1.217130696  0.747908093
##  [325,]  0.1899856372  1.408882499  1.089384490  0.200289816  1.301132506
##  [326,]  1.5306979569 -0.007728883  0.890404170  0.397210270  0.490016103
##  [327,]  2.2893767467  0.318454335  1.725825543  0.907123452  0.824644618
##  [328,]  0.5272583534  0.528452466  0.781370727  1.436842610  1.465604480
##  [329,]  1.3557771211  0.295668121  0.746308941  0.328887343  1.471356929
##  [330,] -0.2387666766  1.693025587  0.894436284  0.469086034  0.651322483
##  [331,]  0.2581662989  0.376892769  0.475893249  0.904753504  0.666346910
##  [332,]  2.6891155457  1.468818714  1.085303887  1.160475724  1.361989752
##  [333,]  2.0524668944  1.066827086  0.539706216  1.629994575  1.228670845
##  [334,]  0.1283643571  0.373286378  1.030416276  1.915324313  0.991129212
##  [335,]  0.4406455625  1.729308533  1.141002047 -0.006806497  0.956252833
##  [336,]  1.0751146615  0.293851005  0.703219724  1.531679947  0.270405588
##  [337,]  2.6366221749  1.208556894  0.909899010  2.739573836  0.312279444
##  [338,]  0.0866368346  0.567908711  0.952618927  0.484394673  0.715903547
##  [339,]  1.1751020146  1.593447987  1.065270699  0.630113897  1.176386152
##  [340,]  1.1404386570  1.262448155  0.543860357  1.138234091  1.486707781
##  [341,]  1.1521715615  1.110950550  0.415563772  1.635031615  0.829906125
##  [342,]  0.6878985343  1.026873748  0.283587616  0.899897787  1.104057652
##  [343,]  1.4401619313  0.266735291  1.039121762  0.274220686  1.306300444
##  [344,]  0.5434021827  0.101005225  0.814193239  0.895308403  1.883687472
##  [345,]  0.2244260752  0.620564398  0.595835154  2.134231789  0.457660095
##  [346,]  0.2530861312  0.254799335  0.974663248  0.995456912  0.570184833
##  [347,]  0.8710243741  0.550925224  1.450611696  1.554835070  1.105464110
##  [348,]  1.4959448144  1.057383415  0.668921542  2.192244594  0.452128426
##  [349,]  0.5896602843  0.751907282  1.748671031  0.564777301  0.031678678
##  [350,]  0.0922683799  1.359486828  0.116223950  1.108716647  0.782406981
##  [351,]  0.6649352910  0.691017037  1.741483616  1.567817009  0.876258959
##  [352,]  0.6881420390  1.487931316  0.603301836  1.736963643  1.757917727
##  [353,]  0.5180937622  1.807654676  1.079716002  0.259258734  1.372066684
##  [354,]  2.3900088796  1.752678958  0.633524614  0.318648050  1.173195688
##  [355,]  2.1886778595  0.339327324  0.468070335  2.333200009  0.350077326
##  [356,]  0.4096380054  1.680284171  1.495011227  0.108151823  0.479490805
##  [357,]  0.4982834017  0.768379904  0.224880608  0.912714798  0.795405646
##  [358,]  1.6571629851  1.399828794  2.360622466 -0.111063033  1.589333428
##  [359,]  0.1985143829  0.595968018  0.351307499  0.323975101  1.599321983
##  [360,]  0.7455406671  0.497021549  0.466368831  0.604546001 -0.083715588
##  [361,]  1.1145721218  1.757877168  0.645600194  2.656473050  0.942366931
##  [362,]  0.9444505495  0.598511927  0.335092764 -0.033989986 -0.082718494
##  [363,]  0.9807963361  1.089720457  1.917042294  0.330176865  1.823119015
##  [364,]  0.1595949399  3.181590750  0.151620021  1.253043632  0.307455462
##  [365,]  1.7256063686  1.682716707  1.668272851  0.923543040  0.218525031
##  [366,]  0.7059573044  1.325625385  0.723136324  0.117258252  1.457522962
##  [367,]  0.6648232186  0.732511362  1.626021044  1.040285273  1.237782884
##  [368,]  1.5579678721  3.387758978  0.615651391  0.791895106  1.070191923
##  [369,]  1.3354867117  0.363804843  1.479020491  0.140239985  3.703152667
##  [370,]  1.1218124215  1.148191093  0.374365749  0.238523196  0.743511225
##  [371,]  0.5228089549  0.358201983  2.975147173  2.725264236  0.766256013
##  [372,]  0.8085240641  0.802511479  0.679138885  0.663154212  0.745832454
##  [373,]  0.4891287756  1.496202726  0.966513203  0.596091071  1.040238802
##  [374,]  0.3337984124  0.145142141  0.489486649  0.278834233  0.602389482
##  [375,]  0.2695320876  0.345969632  2.270840834  0.802864233  0.400534520
##  [376,]  2.6082127329  0.490637801  0.380085883  1.565475868  0.318259759
##  [377,]  0.8793752016  0.621338160  0.322926673  0.329104693  0.818735585
##  [378,]  1.2336873212  3.690980244  1.102409960  0.570787567  0.365442377
##  [379,]  0.0695548143  0.665997128  0.295165136  1.424917208  0.814277684
##  [380,]  1.4259631792  1.491642080  0.181398734  1.193109979  0.861592050
##  [381,]  1.5558417596  2.008356328  0.593270501  0.333028493  1.971625335
##  [382,]  0.3843485048  1.432052057  1.027549291  1.207954495  3.031596148
##  [383,]  0.5482430631  2.302687687  1.000033780  0.526054893  0.560388569
##  [384,]  0.4512693390  1.927284323  2.046065983  1.787911677  0.298373794
##  [385,]  1.2303719995  0.533712653  2.911083489  0.749911865  0.518230628
##  [386,]  2.1669301402  2.733034994  1.032659437  1.213352254  3.817383209
##  [387,]  0.5540588284  0.543203034  0.530910357  0.460647000  0.646468710
##  [388,]  0.4421433976  1.391315078  0.781701358  1.817304957  0.474056638
##  [389,]  0.8168028862  0.084257139  0.192264030  3.688068807  0.178321022
##  [390,]  1.4370648304  1.266943910  0.182239466  0.534196121  3.057080111
##  [391,]  0.9722208971  0.489240832  1.284792105  1.128633438  0.664907283
##  [392,]  3.4451150250  0.146854311  0.847511693  1.955905482  0.527481475
##  [393,]  0.9242333309  0.774348302  0.958932277  1.262947137  0.779777247
##  [394,]  0.8294472434  0.252133528  0.834187008  0.814311104  1.045823867
##  [395,]  0.7247918913  0.768376610  1.876976868  1.439194664  1.301708349
##  [396,]  0.3181842259  0.144796421  0.342571969  0.621705853  0.945660220
##  [397,]  0.8585147133  1.446810556  0.522279490  1.202719565  0.211153250
##  [398,]  1.1517126323  0.711732937  1.599485479  2.352903038  0.778520145
##  [399,]  1.9452530324  1.028001070  2.520936024  0.534768458  2.981643102
##  [400,]  2.0171098969  1.376879890  0.915747957  0.929358137  2.412046996
##  [401,]  0.4527532521  0.914592161  1.739469743  0.606345221  0.464533279
##  [402,]  0.9657401298  2.003348470  0.797094959  0.350172534  1.167627034
##  [403,]  1.0050190026  1.461590079  0.365074919  1.592852838  2.392585369
##  [404,]  1.0543850499  0.798138259  0.791038415  0.805908505  0.740251818
##  [405,]  0.8302611002  1.419162358  0.608188177  0.988345716  1.325755677
##  [406,]  1.1699984129  1.630459681  0.377609245  0.459863693  0.508308020
##  [407,]  0.4501541230  0.476686670  0.259622561  0.553607123  0.613849799
##  [408,]  0.8518458346  1.562959281  2.139338552  0.794507054  0.974452298
##  [409,]  1.3890895158  0.188492099  0.872221554  0.432782270  0.943854892
##  [410,]  0.5628404793  0.835063691  2.925131965 -0.017578575  1.456287922
##  [411,]  0.6011246926  0.932199868  1.469589883  1.536560254  0.958903553
##  [412,]  0.6807369077  2.039510437  0.910386223  3.118435485  1.178457684
##  [413,]  0.5041085845  2.239151978  0.602781901  0.658017730  1.291075644
##  [414,]  1.3692892848  1.231371991  2.677779542  0.247823074  0.791738932
##  [415,] -0.0097507801  1.927488030  1.472581607  0.398929431  0.989611335
##  [416,]  1.0093854819 -0.069074133  2.108460699  0.785140928  0.610682420
##  [417,]  0.1640238635  1.311799323  0.351162724  1.268258186  0.721210479
##  [418,]  0.3546356480  0.106036392  0.619447715  1.074298077  2.470068062
##  [419,]  0.6542078767  2.826300031  0.107878697  1.429430994  3.449194169
##  [420,]  0.2890772824  1.470949735  0.427487023  1.111993305  0.482954720
##  [421,]  2.9171121538  1.531054323  0.422874468  0.263822177  0.098961854
##  [422,]  0.4273022769  0.874480369  0.869986505  0.710490007  2.056742386
##  [423,]  1.0173854990  0.542992173  1.207807368  0.772968018  0.688264749
##  [424,]  1.1160861273  2.097534924  1.087775031  2.070417496  1.152175172
##  [425,]  0.5424998923  1.018665837  0.694768067  1.557314208  1.611400775
##  [426,]  1.8369722998  3.449177557  0.405655355  1.010160823  0.680805942
##  [427,]  0.7252185353  2.529262772  0.881356210  0.881999051  0.607445066
##  [428,]  0.8017932903  2.622480505  0.617939607  1.006755050  0.139311707
##  [429,]  0.1776941253  0.092925709  1.454966582  1.310250896  0.274821609
##  [430,]  1.1906042891  0.597640959  1.323089710  1.496602024  0.577887997
##  [431,]  1.0538518861  0.085633647  1.684231590  0.605921257  1.044054232
##  [432,]  2.0469181384  1.172876554  0.143661466  0.562395701  1.505372086
##  [433,]  0.4413299806  2.450384017  0.388989884  0.446641687  0.575030209
##  [434,]  0.9076449587  1.285053529  1.022208790  0.714759759  0.220553418
##  [435,]  0.2391368336  0.610063748  1.515596898  1.639414380  0.776830505
##  [436,]  0.6108005336  1.306998537  2.440432206  0.562138891  0.661356108
##  [437,]  0.3181720246  1.135657428  0.038966450  1.121832136  0.299126290
##  [438,]  0.7712866831  0.104890459  1.182671704  0.579206461  1.665172821
##  [439,]  0.7680120547  0.939718785  2.343578395  1.854100935  0.023460337
##  [440,]  0.2020921489  0.948917370  0.337176771  0.236459660  0.882549975
##  [441,]  1.7628696577  1.625864877  1.911535583  1.136678600  0.701140900
##  [442,]  0.3557584393  1.503092902  0.201968340  0.533129479  0.384970961
##  [443,]  1.8643140169  0.997793771  0.579346875  2.305517522  0.556805640
##  [444,]  0.7687338843  0.642429635  1.071731641  0.635322536  0.088473572
##  [445,]  0.2208177623  0.713724040  1.145381863  1.027663460  1.222584968
##  [446,]  0.6309421023  2.041027276  0.679668870  0.423665562  0.386396204
##  [447,]  0.6470331094  0.611489885  0.543946960  0.591888760  0.463228209
##  [448,]  0.0669937991  0.714597558  0.304666633  2.327521132  1.211196498
##  [449,]  1.5721773953  0.963003989  0.532591984  1.452032097  0.458720972
##  [450,]  0.5318155235  0.720661874  0.695773556  0.314454022  0.763981283
##  [451,]  0.3510311799  0.720578259  2.050055102  0.518305716  0.590958450
##  [452,]  0.4903969996  2.425910161  0.485997432  0.570000636  1.031151143
##  [453,]  0.1652851229  1.057386992  0.590102107  0.632734197  0.713629800
##  [454,]  1.0816449659  0.913337059  0.671071666  1.899047645  0.972771776
##  [455,]  0.6624404786  1.310767531  1.025491904  0.668436272  0.611432235
##  [456,]  0.1777471293  0.789076035  1.333306429 -0.011938698  1.418158111
##  [457,]  1.1804156341  0.508814859  1.018020861  0.542480667  1.537544722
##  [458,]  0.6726031395  0.927150143  0.958712957  1.365442229  0.122268351
##  [459,]  1.2543608972  2.274922001  0.983366776  0.619852983  1.130163866
##  [460,]  1.4134133714  0.751348063  0.710820142  2.786384512  1.143492314
##  [461,]  0.1894686550  0.339692410  0.906048728  0.439355111  0.530481125
##  [462,]  1.0877950590  1.078945464  0.308946531  0.265779852  1.211610914
##  [463,]  0.9277441138  1.781770092  0.218310930  0.893591054  1.520912699
##  [464,]  1.2237209442  1.363681592  0.543379726  0.390761416  0.357738537
##  [465,]  2.1340004628  1.237833539  1.545705618  0.574994013  0.678917105
##  [466,]  1.1205872792  1.318915957  0.284148190  2.511044275  0.947912361
##  [467,]  1.0399491341  0.260345693  0.934124764  0.414658779  0.873394882
##  [468,]  0.2990985221  0.753367707  0.205573039  0.976511266  1.774663163
##  [469,]  1.7707860203  0.602066610  2.222396732  1.266355906  0.476742094
##  [470,]  0.2953353502  1.328468188  0.354600134  1.164127644  0.571845483
##  [471,]  0.9215194391  0.463456955  0.463591125  0.678766649  1.252587263
##  [472,]  0.4207879561  0.047660347  1.514910126  0.952147966  1.974438779
##  [473,]  0.9999319789  1.419336736  1.880786756  0.796802073  0.450128322
##  [474,]  3.7662862790  1.100570133  0.599040505  2.333490113  0.138866183
##  [475,]  0.2545872852  0.122580357  1.578938026  0.458216259  0.476220185
##  [476,]  0.2499992898  0.725828219  0.965791488  2.283908739  2.141458408
##  [477,]  0.1598628942  0.018021163  1.872742973  0.458841530  0.982954538
##  [478,]  0.9608062112  2.589040980  1.169043139  1.652386258  4.412400885
##  [479,]  1.6694109016  0.324307819  0.773229661  1.526999296  0.236528091
##  [480,]  1.5269757619  0.898307192  1.787885392  0.072191492  1.078540812
##  [481,]  2.1600077218  0.030906917  0.721153555  0.813326978  0.826777846
##  [482,]  0.1058173495  1.002095814  2.139414937  0.596341548  0.258139795
##  [483,]  1.3238648818  0.843478586  1.266190096  0.452592905  1.196349346
##  [484,]  0.2754731209  0.590774852  0.309066526  0.454054216  1.858074333
##  [485,]  0.7372845848  1.524512035  0.213688200  1.877782009  0.370711419
##  [486,]  1.0173751817  1.664041072  1.110289394  1.019850241  0.251909631
##  [487,]  1.5486838400  1.810912959  0.556604211  0.278372356  1.972678235
##  [488,]  2.6911875982  1.050431777  0.634386066  0.504398943  0.971312885
##  [489,]  0.9486810730  0.807479023  1.077328963  1.178773397  0.250926890
##  [490,]  0.6868232267  0.973818263  0.425913227  0.661336387  0.472800226
##  [491,]  0.9495022981  2.184478466  0.663625402  2.176062931  0.641160860
##  [492,]  1.3937131022  1.377834076  1.577598191  2.456602777  1.644905744
##  [493,]  1.6642926659  3.707365528  1.412196306  0.709060423  2.237456535
##  [494,]  5.6131334794  0.546116895  0.987459488  0.098573302  0.850865165
##  [495,]  0.9878120105  1.362289111  1.591486984  1.323956250  1.061963199
##  [496,]  0.4364905086  1.257961174  1.457163131  0.811033740  1.375290120
##  [497,]  0.7018212336  0.768188555  0.583640906  1.890218018  0.260382694
##  [498,]  0.7431768217  1.422883074  0.543034270  1.225489954  0.774898093
##  [499,]  1.2304841660  2.396126765  3.901594408  1.027245914  0.921178227
##  [500,]  0.2054887391  0.493017503  0.628061009  0.817994729  0.977202632
##  [501,]  0.6191795006  0.272979260  0.740385208  1.802262742  0.233953135
##  [502,]  0.0935800120  0.135948077  0.781659361  2.064530957  1.808397954
##  [503,]  0.6936211746  0.231378286  0.897192952  0.220043152  0.594565695
##  [504,]  0.1860318088  1.198703491  0.400704396  0.140231610  0.264236448
##  [505,]  0.3660855963  2.314918695  1.361092139  1.147373182  1.677671805
##  [506,]  0.8994500494  1.180001640  1.900250969  1.272673378  0.520346863
##  [507,]  2.6178199332  0.143131866  0.588044029  1.716581863  1.171188632
##  [508,]  1.3216673839  2.464932620  2.567699249  1.427774712  1.412299479
##  [509,]  0.4870544583  0.404930792  1.630491528  1.550503287  0.584917368
##  [510,]  0.5123810923  1.218776553  0.445717571  1.826292473  1.617802653
##  [511,]  0.4217636691  0.637434938  0.231764968  2.086750837  0.698095464
##  [512,]  1.6111536592  0.697406584  0.967315876  0.596105121  1.162072397
##  [513,]  0.4824415068  0.044170035  0.626685151  1.457062936  1.450074244
##  [514,]  1.8775539804  0.319184781  0.604725337  1.570028923  1.182431007
##  [515,]  0.3017865069  1.126418719  0.577933261  0.357533352  2.057157071
##  [516,]  0.6437358086  1.485996344  1.380355852  1.173789071  1.138649834
##  [517,]  0.4748666271  0.243393792  1.131752149  1.423034187  0.457529187
##  [518,]  1.1468107043  1.329718494  1.646512032  0.241586461  0.824421790
##  [519,]  0.1878411675  0.160778353  1.492217524  0.775309269  0.999627071
##  [520,]  1.0071622667  0.750713922  0.040703436  0.485462699  1.942975723
##  [521,]  0.5005606461  0.593670561  0.754531288  2.030891938  1.003319187
##  [522,]  0.7444325073  2.722869307  2.798096969  0.920688095  0.575838963
##  [523,]  1.6781844682  0.916855836  2.245208194  0.450073801  0.148892512
##  [524,]  0.8672939243  1.107155293  0.559773239  1.390181785  1.920888773
##  [525,]  0.3060499918  1.589167579  0.363173299  1.184536412  0.738430107
##  [526,]  3.2879620262  0.112778467  3.136102594  1.122627926  0.545863797
##  [527,]  0.8926891350  1.290465362  1.347433826  0.301613435  1.054645218
##  [528,]  0.3746072314  1.078885898  1.123556140  1.159850773  1.929252393
##  [529,]  1.7622089563  1.026378931  2.349671964  0.590507304  0.580582388
##  [530,]  1.3886214225  1.961373012  2.554008177  3.437091617  1.083565094
##  [531,]  0.3757420476  0.430700815  0.542565358  0.577933792  0.322298098
##  [532,]  0.4021791996  0.449464316  1.380636049  1.374861191  0.686046336
##  [533,]  2.2522640727  1.049026657  2.201829985  0.943218034  0.990023934
##  [534,]  0.4915158665  1.031853665  1.330536282  0.877642974  0.124023108
##  [535,]  0.2460453632  0.791678982  1.222214987  1.719349913  1.344562205
##  [536,]  0.3237432283  1.598475276  0.705649782  1.524790274  0.999966346
##  [537,]  0.6464689824  1.069142072  3.119695076  1.249468007  0.825789895
##  [538,]  0.8653088355  0.551286803  0.415711083  0.812189097  0.999179047
##  [539,]  0.2564912737  0.279103074  0.776976702  0.521326980  0.597206041
##  [540,] -0.0363129823  0.181706783  0.265574668  0.957983228  0.379320025
##  [541,]  0.2019689295  0.875637872  0.225109578  0.573276461  0.403001688
##  [542,]  2.4420480751  2.895851023  1.384766013  0.998676871  1.023491559
##  [543,]  1.4668537581  1.261661927  2.227989682  0.491051165  1.046840632
##  [544,]  0.2700307786  2.143296220  0.781251623  2.659583062  1.276899510
##  [545,]  0.1281894571  1.003611702  0.767434124  1.476263280  2.585063293
##  [546,]  0.4954587649  0.812427572  0.651116198  0.983717411  0.486377310
##  [547,]  1.4042226473  0.702359795  0.313622845  1.066724888  0.799827758
##  [548,]  0.8451659681  5.523082962  2.404743210  1.377050580  3.083064852
##  [549,]  1.0634708645  0.734012063  0.232526874  1.007031851  0.945602958
##  [550,]  1.4108409420  1.636751213  0.681941914  1.376862077  0.759372526
##  [551,]  1.2306678619  1.513027039  1.710370070  0.632566822  1.356430023
##  [552,]  2.4000061165  2.294203264  0.700934112  1.283697062  1.054354597
##  [553,]  1.6334395512  0.956520177  1.397373313  0.438907305  0.523283950
##  [554,]  1.5252586117  1.278719724  1.572154417  0.214420365  0.360528212
##  [555,]  0.8116642473  0.569024036  0.733437737  2.098933655  0.777533565
##  [556,]  0.7908677739  0.639140939  0.529410977  0.021639210  0.537161298
##  [557,]  1.4724916250  0.684230923  1.135954117  1.012899084  0.797109374
##  [558,]  0.8534801758  1.570853295  1.136653366  0.442246153  1.314486779
##  [559,]  1.6140260625  2.232925570  0.286875292  1.891879547  1.011681571
##  [560,] -0.1031158746  2.598105506  1.182767157  1.585889279  1.274405234
##  [561,]  0.3673178481  1.503437355  0.102981063  1.858427958  1.032750787
##  [562,]  0.7122744949  0.397098244  0.577986793  0.035790542  0.384115543
##  [563,]  1.0973666785  1.658422449  1.046222984  1.692491299  0.097860182
##  [564,]  0.9107346263  1.107249674  0.286234669  2.534264417  1.801197120
##  [565,]  0.8194870911  0.954224476  0.360818697  0.401457443  0.257978815
##  [566,]  0.7120160969  1.197757650  3.039001790  0.617144511  0.459496492
##  [567,]  0.8283656105  0.292218921  0.923033729  0.605855815  0.785154133
##  [568,]  2.0730892198  0.530931878  2.096287557  3.292587550  0.984808138
##  [569,]  0.2164192056  0.613643047  0.877240963  0.819696116 -0.040966241
##  [570,]  0.3959397066  0.992043524  0.941352772  1.125282903  0.681860017
##  [571,]  0.5132557278  0.431563907  0.702343705  0.576043685  1.009679362
##  [572,]  0.5699804548  0.824723536  2.608663515  1.614676141  1.278692260
##  [573,] -0.0057003451  0.179632520  1.202810615  1.014683185  1.002133090
##  [574,]  2.2636598344  1.783769359  1.571614354  0.518415657  1.730455729
##  [575,]  0.8600937717  0.358296577  1.000618753  1.048755560  0.371686073
##  [576,]  0.7992414116  0.429109974  1.336520769  0.535037708  1.110139691
##  [577,]  1.0811280239  0.804533041  1.339532815  2.921094839  0.194988710
##  [578,]  0.8433742591  0.497239123  0.873239441  2.060299264  0.377956695
##  [579,]  1.4873836714  1.500780451  1.143182609  0.467974104  0.554819423
##  [580,]  0.4932403006  0.144581419  0.273657585  0.404465004  0.454358045
##  [581,]  2.4827713034  2.165294080  0.834995283  0.894716082  0.558936438
##  [582,]  1.0623846930  0.963327534  0.412197624  2.758041253  0.288025700
##  [583,]  1.0012175919  1.199126403  2.407043650  0.857200911 -0.004171599
##  [584,]  0.2142276994  1.510110534  0.415902513  0.219376464  0.170871851
##  [585,]  0.6091789917  0.783174717  0.148589791  1.546950009  0.558815596
##  [586,]  0.8558434156  0.094290188  0.764461469  0.372312645  1.141057067
##  [587,]  1.1016191167  0.163719445  1.320360471  1.739042783  1.125008484
##  [588,]  1.6592787654  1.193795813  0.584406848  1.170896509  0.444719568
##  [589,]  0.4850471361  1.900826293  0.641916727  0.164214303  2.035883983
##  [590,]  1.1034923020  1.339006201  0.665112697  0.831911689  0.457591534
##  [591,]  1.7550077466  0.696647505  1.899731575  0.716533386  0.820859974
##  [592,]  0.6190457855  1.258421206  0.376604731  2.883186021  0.169152430
##  [593,]  0.8544563552  0.418665933  0.591803197  1.310920776  0.501146551
##  [594,]  0.7612229114  0.687694755  1.661713190  0.277964325  1.283014367
##  [595,]  0.5473463348  1.721185917  0.488168366  0.567449731  1.267000365
##  [596,]  2.5911196669  1.087225500  2.239207698  1.525156694  1.689132552
##  [597,]  1.4233840621  2.205389856  1.583636634  1.909261256  1.221078066
##  [598,]  0.4741080030  0.979096545  0.373828127  1.746253880  1.698177140
##  [599,]  0.7061135230  0.986449072  0.450472620  0.780511843  1.267429518
##  [600,]  0.7111475172  0.706462476  0.952169757  1.309086643  0.681669755
##  [601,]  0.1585539830  1.138629389  1.441338492  0.759755944  2.099820747
##  [602,]  0.3372908852  1.079451295  0.355695578  0.963677335  0.731796146
##  [603,]  1.1697027923  0.374787466  4.468828871 -0.114154562  1.194550888
##  [604,]  0.7997449577  1.366955324  0.916239539  0.542573346  0.495989067
##  [605,]  1.4453607368  2.044051697  1.011765818  1.604979974 -0.003865148
##  [606,]  2.0329510007  0.971403861  1.159211071  0.538854410  0.877150850
##  [607,]  1.9559738324  0.650860694  1.130236756  0.806995129  0.998147581
##  [608,]  1.1554569307  0.738761201  1.010991000  2.198516179  0.583239935
##  [609,]  1.1718840297  0.523711606  0.681189324  1.716548684  0.469216859
##  [610,]  0.3319203136  0.695629902  0.990115124  0.330978340  3.556665771
##  [611,]  0.5022036002  0.667374405  0.154333667  0.394418823  0.835113967
##  [612,]  0.0674614166  0.070915492  0.031683180  0.309200512  1.099692901
##  [613,]  2.1103941825  0.321661129  2.509872140  1.790253889  1.813178055
##  [614,]  0.4437510620  0.145648832  0.268726244  0.039685703  0.515026848
##  [615,]  0.7705782256  3.406480315  0.428256456  1.084272304  0.318685287
##  [616,]  0.3437478799  0.677200254  1.465243285  0.196117538  0.122713907
##  [617,]  0.8335610011  0.794129932  0.882136066  0.417200207  1.040317535
##  [618,]  1.5493110082  2.245187723  0.265800584  0.440110216  0.717861865
##  [619,]  0.5354290819  1.666593499  0.992317793  2.799348817  0.335289926
##  [620,]  0.7108859531  2.275240918  1.120721404  1.810775736  0.335191801
##  [621,]  1.9390599564  1.791264473  1.162882280  0.652558460  0.663720244
##  [622,]  0.6641657811  0.913190895  0.310721622  1.345890539  0.183888559
##  [623,]  2.7463817184  0.149579580  0.706208298  1.689248926  0.776921515
##  [624,]  1.3104906736  1.418205389  2.892980079  0.073305023  0.557054099
##  [625,]  1.6095672486  1.902029742  2.021906975  1.457078856  0.730562068
##  [626,]  2.3834257904  0.900347910  0.651100358  1.087916621  0.824289929
##  [627,]  0.7067984833  0.445776384  1.016585938  0.626009443  1.115849601
##  [628,]  0.1620571708  0.519946690  0.145667100  0.779839809  0.466403588
##  [629,]  1.0113055740  0.847049255  1.388530118  0.036960314  0.829275600
##  [630,]  0.4306068252  0.945990422  0.744636536  0.865181157  2.738993663
##  [631,]  0.2914551723  1.772441638  2.094757296  0.626605765  1.366552964
##  [632,]  1.2277085022  0.071391894  0.196704541  1.207900659  3.960077076
##  [633,]  3.9054624138  1.708126132  0.719126498  1.514566567  0.591290881
##  [634,]  0.3450810646  3.752554502  0.517878291  1.066745551  0.334681475
##  [635,]  0.9564948624  0.554726348  0.479775774  0.584308157  0.638517090
##  [636,]  1.6442780421  0.319496958  0.313719323  0.375718536  0.449735900
##  [637,]  0.4727919715  2.654897259  0.247354274  1.551849398  0.112605303
##  [638,]  0.2287243268  0.678675540  1.090847652  1.059421585  1.228426794
##  [639,]  0.3680019152  0.828469415  0.245933128  0.392102430  0.029989583
##  [640,]  0.3784098989  0.217530612  0.489617331  2.061552857  0.867598941
##  [641,]  2.6042171863  0.810548109  0.315585419  0.180404305  0.327803066
##  [642,]  0.0504409698  1.378920582  1.155320643  0.048379139  0.890436789
##  [643,]  0.7189621206  1.145052699  1.717363728  1.247984785  2.020200615
##  [644,]  0.9646387952  0.901899728  1.903495352  0.710593729  1.019056309
##  [645,]  0.8564946338  0.230715933  1.620639978  1.229096808  1.751631890
##  [646,]  2.0061891885  0.649726935  0.301533503  0.164174306  1.653570157
##  [647,]  2.1384075818  2.039418404  0.997551899  0.910927761  1.241639316
##  [648,]  0.8592357174  0.336652385  0.558360988  0.465745643  0.094537514
##  [649,]  1.6388401501  1.172733274  1.168049314  1.014708295  0.688290916
##  [650,]  0.3909373082  2.156736629  0.233574090  0.966699833  1.342182545
##  [651,]  2.1067828761  2.160969160  1.443575118  0.440052478  3.771151296
##  [652,]  0.3958963097  3.221285419  1.906786312  1.253378694  0.081166307
##  [653,]  0.1569555722  0.547271758  2.225036800  1.075629849  0.425725752
##  [654,]  0.4947606340  0.365371916  0.833981214  2.325541656  0.211070645
##  [655,]  1.4042129079  1.036033356  0.270114297  1.468922425  0.759714983
##  [656,]  0.1802105244  1.354093546  2.069646249  0.544562840  1.709869038
##  [657,]  1.4670005377  0.866440404  0.273500579  0.430327978  0.637296584
##  [658,]  1.1265256215  0.969746391  1.379463310  0.388077806  0.404460439
##  [659,]  1.6127872842  2.905614561  0.850159795  1.280914362  0.284646111
##  [660,]  0.5044504767  1.336340853  0.152398273  0.306193842  0.808127085
##  [661,]  0.4154071207  2.278140322 -0.088174111  0.750838098  0.557876609
##  [662,]  3.1264000128  0.440068072  0.341951306  1.069138043  2.884496148
##  [663,] -0.0292876178  0.589505385  0.199177054  1.286604471  0.813619642
##  [664,]  0.5738326871  0.623012356  0.750555558  1.009269883  1.433394378
##  [665,]  0.3492919006  0.453048770  0.188023927 -0.066382888  0.639448084
##  [666,]  1.4837607849  0.957177516  0.374657050  0.598640242  0.320067216
##  [667,]  0.8793416598  0.985360869  0.672217148  1.060402757  0.997817020
##  [668,]  1.9716111256  3.651704106  0.802063814  1.350102744  1.194630750
##  [669,]  1.0801564371  0.346609511  0.745337814  0.838050776  0.455966884
##  [670,]  0.6612525143  0.312891452  1.652802486  1.224440965  2.256425617
##  [671,]  2.3665696624  0.909522901  0.321586608  0.471098869  0.970111520
##  [672,]  0.5405645338  0.010976401  0.937864576  1.519332652  1.730627385
##  [673,]  0.1102504485  0.251033372  0.374192225  0.482889117  2.153515879
##  [674,]  0.9731456280  0.889933831  1.792546179  1.001685490  0.286758801
##  [675,]  1.6341424068  0.651073077  2.200941240 -0.101415688  1.145026886
##  [676,]  1.3005419012  1.750784714  1.002548509  1.036225822  0.199809872
##  [677,]  0.3278153333  1.027533836  0.486375034  0.824453097  0.184722565
##  [678,]  1.3433443688  1.079086237  1.845832103  2.138328628 -0.110753485
##  [679,]  0.4833430885  0.524733194  0.385101535  2.511148219  3.414226892
##  [680,]  0.6817627865  0.929619479  1.205857415  2.220422159  0.873657176
##  [681,]  0.6816987330  0.769335531  0.011954681  0.713494120  1.029496119
##  [682,]  2.5014354187  1.215723422  1.337060744  1.417244915  1.298396058
##  [683,]  0.2369194054  1.252479725  0.245156064  0.737835342  1.157697936
##  [684,]  2.2814677649  0.769883766  1.880589586  0.352491903  2.108816844
##  [685,]  1.1573292978  1.204165436  0.716697688  0.174745089  0.387914292
##  [686,]  0.8580740045  1.203836741  1.627572670  0.292925255  1.320548248
##  [687,]  1.3411921587  1.310736003  0.478786984  1.407684790  1.615822744
##  [688,]  0.7797890343  0.504946533  0.831128162  0.049694313  0.823702902
##  [689,]  2.0034143073  0.581170095  0.097270231  2.042365143 -0.217175080
##  [690,]  1.2586041368  1.190099785  0.063931219  0.797821491  1.326351661
##  [691,]  1.2278358985  0.458633252  2.759040433  1.657379864  0.344079670
##  [692,]  0.4831836379  0.407301843 -0.008391736  1.446589029  0.244652892
##  [693,]  1.5669534273  1.254118149  1.427864317  1.078123396  1.224149100
##  [694,]  0.7177198107  0.700348764  1.807746121  0.677371648  0.690493516
##  [695,]  1.8287325483  0.371997536  0.929456430  2.510082561  0.783095416
##  [696,]  1.5689703838  1.348714843  1.598488657  1.883659993  0.628558902
##  [697,]  0.8998225317  0.405418899  0.276647558  0.880347886  0.341027895
##  [698,]  1.9296478721  0.992981336  0.574586234  0.188267412  0.484053346
##  [699,]  0.4110339047  0.995653255  0.855443012  1.278064043  1.993389270
##  [700,]  0.4525450530  0.833889375  0.190621981  1.384704944  1.467452141
##  [701,]  1.5079023620  0.882681056  0.135981731  0.819689272  0.427907692
##  [702,]  1.4230512255  0.557654740  1.001788412  1.080348393  1.166521247
##  [703,]  0.6944946463  0.894928745  1.085612605  1.093530494  0.947067438
##  [704,]  1.1070399777  0.823416178  1.118446486  0.415954570  1.458413372
##  [705,]  1.7117805650  0.608787817  0.996357390  0.835148469  1.910032361
##  [706,]  1.0922363185  0.683620917  0.417674477  1.369768195  0.649033712
##  [707,]  2.0093622078  0.349004524  0.895719120  1.438484730  0.711936531
##  [708,]  0.8960897785  0.610947175  1.339962890  1.299966695  0.245909792
##  [709,]  1.0354973589  0.766599751  1.024467940  0.318195973  0.712189374
##  [710,]  0.3126788495  1.251339881  1.458234698  0.952418763  0.214415294
##  [711,]  1.4393797996  0.528357102  0.576872183  0.362223964  1.317373578
##  [712,]  0.3983139743  0.462462929  1.784733502  1.422804339  1.579070923
##  [713,]  1.1295257842  0.452236498  0.566847724  0.020558448  0.459990230
##  [714,]  0.9337698295  0.751894171  0.261671576  0.460855055  0.939974144
##  [715,]  2.7125837270  0.879683510  0.154498324  0.998546228  1.128361625
##  [716,]  0.9832347627  1.221201350  0.604002582  0.532347506  1.235936787
##  [717,]  1.2073781176  2.291197584  0.652600926  0.441423128  1.491416994
##  [718,]  1.1488504638  0.176732041  0.653357328  0.053416565  0.090032334
##  [719,]  0.8015541591  0.976920053  1.620257074  0.562171661  2.265087027
##  [720,]  0.9537895957  2.561818378  3.166330069  0.999347388  0.703454600
##  [721,]  1.3082923553  1.654460951  0.934779828  0.390163781  1.187124154
##  [722,]  0.2501744957  2.566549805  1.160396946  0.921867171  2.108404353
##  [723,]  0.2403173191  0.521709384  2.079033604  1.427114562  0.918296402
##  [724,]  0.9229794169  0.545578837  2.510029430  0.727119916  0.260788929
##  [725,]  0.1543077424  0.236389255  0.235943726  1.765099287  1.892000006
##  [726,]  0.5514852262  0.449145844  0.848055963  0.942427683  0.790053723
##  [727,]  0.2115329962  2.119891845  0.250616240  1.562830826  0.143198895
##  [728,]  2.4976513521  0.610233015  1.514247632  0.132443776  0.385302563
##  [729,]  0.5840777690  0.941342725  1.256210224  0.714432731  0.574346200
##  [730,]  0.3930202564  0.382591264  0.783143637  1.476220715  3.102546928
##  [731,]  0.4056728935  1.605685431  0.856967887  0.186655229  2.009452610
##  [732,]  1.4471985157  1.250674198  0.774084387  1.732646214  2.757197344
##  [733,]  0.4516170960  2.005463042  0.921323697  1.800877960  0.645132815
##  [734,]  1.3184109275  1.515848811  0.839820953  1.001532182  2.842636901
##  [735,]  1.8686627040  0.440493799  0.706611684  1.185854473  2.931724649
##  [736,]  1.4393289215  1.625828559  1.687340667  1.024348629  1.052253072
##  [737,]  0.4292300218  0.125377325  0.474200237  0.324475682  0.481283583
##  [738,]  0.7003880787  0.283753667  0.674767197  1.771814297  0.332293567
##  [739,]  0.2959528877  0.877930873  0.797338550  0.731434524  0.503775171
##  [740,]  0.6167053098  0.357963331  1.183886887  0.345569232  0.373203188
##  [741,]  0.7826802434  0.958498579  0.284371454  0.968634718  1.130591475
##  [742,]  0.0078082079  0.746744395  1.585713210  1.483319249  1.185972240
##  [743,]  2.9066020930  1.733585722  0.953941899  0.452462588  0.865389060
##  [744,]  1.7483101947  2.376369171  1.700839792  0.643087667  1.981222167
##  [745,]  1.0813088067  0.610408271  0.566992774  0.943736122  0.461570949
##  [746,]  2.9303694586  2.248525309  3.317869088  0.771070391  0.179546996
##  [747,]  0.1859961386  1.770376418  2.320121857  1.547928928  0.416288810
##  [748,]  0.7352184131  0.848308496  0.146638746  0.887463383  0.865366606
##  [749,]  0.2612471973  0.834082252  0.129968560  0.973047249  2.586836827
##  [750,]  0.7805410797  1.008321082  2.066049646  0.416567348  1.729381714
##  [751,]  2.5695079403  0.473113364  2.162002493  0.510154067  0.595815135
##  [752,]  1.6167092624  0.861033502  0.050010404  0.362359553  1.242429902
##  [753,]  0.9991223646  0.403529133  0.855144925  0.297357886  0.679366577
##  [754,]  1.3977280539  1.082427170  0.652848364  1.038262805 -0.080043554
##  [755,]  0.4196802064  0.257278682  0.401685929  1.577401507  1.815405975
##  [756,] -0.0395643307  0.819560967  1.261963866  0.969631693  0.910389304
##  [757,]  0.3849346455  1.556849828  0.518990048  1.603103909  0.427750712
##  [758,]  1.7541782018  1.188482800  0.264167983  0.660384669  1.304728066
##  [759,]  1.1641375017  0.846600582  0.639623351  1.406025473  0.717849574
##  [760,]  0.8121430784  1.803733450  0.786072020  0.992790354  1.002888270
##  [761,]  0.7667013064  0.310913841  0.347710064  0.687485301  0.129699988
##  [762,]  0.7801750041  0.379542653  0.567418014  0.578628071  0.704258322
##  [763,]  1.1638407792  0.134581145  0.877216733  0.837083513  0.274687231
##  [764,]  0.4061153171  1.619100967  0.266968745  0.584528856  0.636571488
##  [765,]  0.3782654681  1.027153629  0.784125097  2.531020559  1.529500886
##  [766,]  1.1744364432  0.745736774  0.447862752  1.489193228  1.466269154
##  [767,] -0.0645346733  2.330588223  1.178341288  2.788745183  0.460144094
##  [768,]  0.5760547036  3.152982222  2.876281888  1.827378937  0.635425761
##  [769,]  1.6994982119  0.762109331  0.632020781  0.802296682  0.505485866
##  [770,]  0.1361481521  1.146306036  0.201586700  0.743040460  0.319014085
##  [771,]  2.5123475690  0.521280514  0.291824340  1.800762492  0.136285959
##  [772,]  1.1244993698  3.766533284  1.706596942  1.213544838  0.582158779
##  [773,]  1.0661812111  0.279674588  1.197799445  0.806235516  0.993548179
##  [774,]  4.0851041664  0.904974943  1.940240176  1.151520232  1.210925799
##  [775,]  2.2200647679  1.890321554  0.929815521  0.151613053  0.801325627
##  [776,]  1.2564557175  0.052230334  0.167275055  0.803300581  0.364304319
##  [777,]  0.2481686320  1.056481798  1.639080800  0.406036062  0.846065158
##  [778,]  1.0478500152  0.173529172  2.007778275  0.434188278  0.795598404
##  [779,]  2.8737915156  1.909323009  0.331442209  3.536880422  0.652403259
##  [780,]  1.5477473444  0.384094386  0.811324336  0.069965959  0.809353380
##  [781,]  0.6761051937  0.139008658  1.683138951  0.419515068  0.365331352
##  [782,]  0.1128518244  0.106464774  0.662870484  0.261035049  1.457031896
##  [783,]  0.7650004389  0.657963338  0.626259876  2.311907562  1.470874655
##  [784,]  1.9970719625 -0.091910671  2.300226218  2.220093206  3.507659993
##  [785,]  0.7940707699  0.343122652  1.066094431  0.805920464  0.818716137
##  [786,]  0.8960241348  1.756770082  3.793897807  1.630754557  0.581788720
##  [787,]  1.5249049331  1.521362849  0.849175252  0.726501998  0.262771053
##  [788,] -0.0255629711  2.030909965  1.907423241  0.851876517  0.804722321
##  [789,]  1.3966482007  0.682551640  1.377467881  0.861545898  0.935494157
##  [790,]  1.2493703713  0.189601214  0.911409332  1.053631471  0.669224429
##  [791,]  0.3046979636  1.352584885  0.271273593  0.239862083  0.170947739
##  [792,]  0.4643290011  0.519527608  0.455725991  0.072826900  1.634868830
##  [793,]  0.8401367813  1.756636879  0.573776062  0.691935913  3.072885290
##  [794,]  1.7655131816  0.805461509  0.278186786  0.845896689  1.505477784
##  [795,]  0.6598945076  0.717407340  1.085712461  2.350876818  0.716789794
##  [796,]  0.9243352178  0.780286410  0.156026201  1.184221624  0.510475387
##  [797,]  0.5317140019  1.711115793  0.490262839  2.415592922  1.136480834
##  [798,]  3.0409126241  1.656225858  0.670685253  0.736828384  2.330239067
##  [799,]  1.4989836822  0.880767133  1.042667643  1.079417904  0.761967344
##  [800,]  1.2981859250  0.423895128  0.373596780 -0.013047757  0.640278423
##  [801,]  0.2810393776  1.472246611  0.831692662  1.063752404  0.983497937
##  [802,] -0.0004136254  2.798462018  0.863649672  2.429504790  0.801670843
##  [803,]  0.9517629957  0.423931646  1.792154718  1.402056701  0.873679448
##  [804,]  1.1594620491  0.801329090  3.502169263  2.303276501  2.522215629
##  [805,]  1.5656275105  1.642064926  0.878280576  0.358760739  0.336575778
##  [806,]  0.4213375808  0.823199475  1.554549847  0.807815444  1.804643273
##  [807,]  1.0145491543  1.422268752  0.525650952  1.343513890  1.631319160
##  [808,]  4.7969425462  0.975190319  1.224474761  0.868103438  0.612783117
##  [809,]  0.7603446160  1.188632674  0.327558404  0.191883400  0.322844599
##  [810,]  1.0329656927  1.842706654  1.243269104  0.467883724  0.650794065
##  [811,]  2.0275375372  0.675259178  2.158436695  0.971331857  0.749504158
##  [812,]  1.3816986181  0.818651370  0.032079230  0.920854125  0.454053356
##  [813,]  1.0212277236  0.303389021  2.917440985  0.604947552  0.775615828
##  [814,]  1.2638534333  1.097881140  1.244657854  0.614990591  1.233006737
##  [815,]  0.1571950728  2.090048427  1.389087779  0.236260471  0.913436552
##  [816,]  0.6295440203  0.007309081  0.607215336  0.609960856  0.094343795
##  [817,]  1.1572463636  0.098276971  0.102854210  0.353320219  1.181930272
##  [818,]  0.2108290903  0.796369904  0.404304156  0.908473710  0.158366038
##  [819,]  0.9426036334  1.055140637  1.135151301  0.895066382  2.847487471
##  [820,]  0.8547362747  1.824275157  0.356172331  1.851866454  1.288761361
##  [821,]  0.3608330171  0.295514345  0.714028559  0.245340885  0.353914553
##  [822,]  0.9578516845  2.053663850  2.197976939  0.623182218  0.744128804
##  [823,]  1.4159298149  0.866011999  1.281440257  1.592963407  0.256251162
##  [824,]  0.4034256257  0.569122426  0.533896281  1.680629803  0.823226443
##  [825,]  0.7051911371  0.163213838  1.011775635  0.446686139  1.093554134
##  [826,]  1.3738597446  0.417742638  1.842738147  0.972101142  0.067958640
##  [827,]  0.6291394771  1.016155963  1.174584640  1.088698621  1.495648455
##  [828,]  1.3371361922  1.111729379  0.463421550  0.791782282  0.781023243
##  [829,]  0.6587814373  1.642217628  2.437860045  0.829123600  1.492062188
##  [830,]  0.2160765738  0.845688745  1.900682888  1.533839832  0.214976551
##  [831,]  2.8333564187  0.803699470  0.955262928  1.374324191  2.394286475
##  [832,]  0.4729640873  0.752438142  0.726110591  0.909883634  1.401523861
##  [833,]  2.0350129870  0.955743306  0.192017328  0.871362588  0.698041051
##  [834,]  1.3161329263  0.276727292  0.582969678  1.390073853  4.022103038
##  [835,]  0.8933036050  0.641575397  0.982463239  0.180207394  1.328717888
##  [836,]  1.5524032735  1.140408723  0.139110586  1.290176789  1.957659316
##  [837,]  0.7011674669  0.194346528  0.449561866  1.599005250  0.583761955
##  [838,]  1.1721515329  0.342349963  0.709482646  0.572498187  0.712914609
##  [839,]  1.5969784584  1.361142959  0.766739649  1.497270078  2.121898923
##  [840,]  1.3994486999  0.398190139  1.529198227  0.555048867  0.470192999
##  [841,]  1.4713658103  0.637836816  1.023645290  0.285028261  1.313335689
##  [842,]  0.4562303007  0.467870223  1.335315363  1.381739051  1.162934461
##  [843,]  1.1813672666  0.410404533  1.021055767  1.129962107  0.194681813
##  [844,]  0.2769824363  0.995692325  0.845327339  1.173013734  0.170869428
##  [845,]  1.0384313478  0.795373467  1.550164965  1.269681965  0.420450922
##  [846,]  0.3101085293  1.152742397  1.598845305  1.197514526  0.647780694
##  [847,]  1.5188166532  2.847539418  0.856485126  0.705489892  1.048959031
##  [848,]  2.6937032193  0.342951456  3.394146870  1.441030492  1.466797853
##  [849,]  1.4448849560  1.149832625  1.618292509  0.555333240  1.615096926
##  [850,]  1.0065833054  0.997968733  0.748712475  1.505246901  1.844081424
##  [851,]  0.3461451264  0.605785464  3.534321296  2.023453969  0.679281547
##  [852,]  1.4345957612  2.379308218  1.371393291  0.832437880  0.531388581
##  [853,]  1.6591141415  0.873031471  0.392706627  0.659180159  0.796361516
##  [854,]  0.0980450073  0.732598894  0.670053622  1.193887925  0.610504042
##  [855,]  1.2358118821  0.949704872  1.217985034  1.858715756  1.921480167
##  [856,]  0.2493727160  0.276041379  0.480369550  0.269636129  0.617919755
##  [857,]  1.3263984380  0.907118133  1.498593247  0.553477558  0.733005609
##  [858,]  1.9398322999  1.395794300  0.082628268  1.522234939  0.755236064
##  [859,]  0.0302511551  1.493982706  1.429679268  1.190416393  0.227426422
##  [860,]  0.1717939757  0.345742503  0.339773555  0.320653883  0.878721627
##  [861,]  1.2282241338  0.986052293  0.199353908  0.856209682  1.580266599
##  [862,]  1.3073583115  0.326011589  0.910079938  1.754624542  0.336068545
##  [863,]  0.8944579250  1.203566446  0.368831563  3.203623355  0.827672247
##  [864,]  0.2943048228  2.379036333  0.324486623  1.486193734  0.825160572
##  [865,]  1.1926479050  1.979562848  0.861009731  0.689092680  0.142215377
##  [866,]  1.9747843280  0.881089569  0.550938297  1.375343973  0.581397727
##  [867,]  1.3624230937  1.662009221  1.130187391  1.189382752  0.660521100
##  [868,]  0.2736299267  0.338694752  0.258557532  0.180246269  0.565818003
##  [869,]  0.4458673745  0.182790084  0.965702220  0.393115792  1.695590663
##  [870,]  0.5223137841  0.672991404  0.352282903  3.422313940  0.003859494
##  [871,]  0.2206042046  1.564773577  2.159979900  0.823342720  1.296793549
##  [872,]  0.4056403823  0.960858322  0.582028599  1.542124650  0.364559839
##  [873,]  1.3155376951  1.276201414  0.547281494  0.534430820  0.887591046
##  [874,]  0.7049403619  0.675937396  0.599413140  1.908318663  0.727683012
##  [875,]  1.8901537792  1.511312029  0.777297766 -0.082702011  0.804671380
##  [876,]  0.0589728930  1.528051822  0.889175765  0.255927910  0.565940572
##  [877,]  0.6739287113  0.512823658  1.103124880  0.777528187  1.889742303
##  [878,]  0.7034571196  0.969451684  0.471316199  1.418713238  0.040960155
##  [879,]  0.4908354829  0.929403804  0.469598564  0.182682734  1.255514762
##  [880,] -0.0220345055  1.708954289  0.883860013  1.595214275  0.540626441
##  [881,]  2.7363462761  1.727920143  0.900482032  1.017015716  2.098130862
##  [882,]  0.4668823424  2.502246258  1.920893494  0.505655418  1.171160741
##  [883,]  0.8665883260  0.770155881  1.947507424  0.586910316  0.993653626
##  [884,]  0.5340082006  0.582955870  0.350970498  0.005354939  0.449721880
##  [885,]  0.4993861095  1.171436872  0.866354986  1.052600848  3.142533983
##  [886,]  2.2679138320  1.143497000  0.104914944  2.630959454  1.203796170
##  [887,]  0.5469737983  0.520775892  0.990237988  0.401079581  0.870553379
##  [888,]  2.0676325514  0.433223596  1.197390484  0.419259831  0.891119936
##  [889,]  0.1768797436  0.251162745  1.755177198  1.389831116  0.029745106
##  [890,]  1.8625214559  1.769834533  0.668498292  1.374310828  0.810065299
##  [891,]  0.7829891958  0.993391683  3.917717578  1.963754459  2.226860259
##  [892,]  2.3353627109  0.884362264  0.453055816  4.613803119  0.811950006
##  [893,]  0.5416258935  1.083922771  1.158891272  0.178326218  1.037420580
##  [894,]  0.4517867828  1.633456604  0.200262009  1.427239039  1.026904488
##  [895,]  0.4364672173  1.640863124  0.927459539  0.776273828  0.603179880
##  [896,]  0.7972482147  2.824925361  1.147468269  2.182130306 -0.058057293
##  [897,]  0.2333079968  0.892624682  0.403502717  1.494945150  0.927117918
##  [898,]  2.0446753314  0.615732284  1.184824245  1.954243747  3.960286978
##  [899,]  0.6036323685  1.020388655  1.177312224  0.974664733  0.276152660
##  [900,]  0.8685923101  1.480330268  1.605519343  0.354756471  1.113189662
##  [901,]  0.7756347907  0.706854590  0.483602253  1.233984077  1.694020197
##  [902,]  0.5514464724  0.540603297  1.041994015  0.520688631  2.247262268
##  [903,]  0.8128852437  0.563754347  1.031634707  0.706177616  0.674352275
##  [904,]  1.0447550454  1.489606085  0.940096069  1.166252880  1.479980377
##  [905,]  0.2229589330  0.345509482  0.912886833  1.895347039  0.493707475
##  [906,]  1.7015672686  0.279332805  1.897877072  1.673766565  0.927032296
##  [907,]  0.9046979119  1.858025855 -0.054419602  0.232157206  0.655375170
##  [908,]  1.4480858691  1.515773035  0.901692989  1.253162771  0.408312106
##  [909,]  0.7772875248 -0.014047522  0.385436159  0.479963844  0.188872364
##  [910,]  0.2168397635  1.649656571  0.796722450  0.243918961  0.514341451
##  [911,]  2.0288146484  1.883438493 -0.054687026  1.271388611  1.517546800
##  [912,]  0.5814565420  0.699459805  2.412018066  0.625013899  0.802336905
##  [913,]  0.5487160081  2.074309525  0.368972852  2.730649580  0.831309231
##  [914,]  0.8844160921  1.006296133  0.394295643  1.612424427  0.542606193
##  [915,]  1.6659152969  0.863549289  2.053024344  0.443875904  0.426826391
##  [916,]  0.9441063428  1.422667817  2.717157823  1.008862123  0.301807697
##  [917,]  1.1110925328  1.576368465  0.426080633  0.815162717  2.505342155
##  [918,]  0.2324531573  0.864194385  0.511765145  2.209715732  0.746080579
##  [919,]  3.4631439781  1.044004607  0.564554698  1.520938551  1.008414208
##  [920,]  0.3739813630  0.935509074  0.555951645  0.115331828  0.616368616
##  [921,]  0.5551040279  0.380190662  2.430881310  1.514002297  0.256408051
##  [922,]  0.8368854804  1.664865700  0.788971147  0.331888747  0.353472875
##  [923,]  1.1283472558  0.382274760  0.619205623  2.026255215  2.005202764
##  [924,]  0.8740213691  0.157428974  0.861780643  0.711795489  0.676334935
##  [925,]  0.3262900254  1.468089548  1.240330788  1.222214116  0.249961148
##  [926,]  0.6875137370  0.487589900  0.702102258  0.438370318  1.424170209
##  [927,]  1.1811769913  0.836186740  1.216435967  1.469473044  1.483477177
##  [928,]  2.5391295160  0.233187861  0.062755166  0.213510397  1.244216862
##  [929,]  0.8560526733  0.561794311  0.228876491  0.669268916  2.971263209
##  [930,]  1.7459757037  1.023082427  1.388180645  0.377878600  1.183254090
##  [931,]  1.1379542064  0.860167144  0.417877876  1.300879122  2.898852774
##  [932,]  1.3948831199  0.832058382  1.881137789  1.269132240  0.719152858
##  [933,]  0.4691290793  0.781254172  0.678491094  0.165908953  0.822705059
##  [934,]  0.1130011398  0.266599844  0.068354514  0.608538662  1.033414388
##  [935,]  2.3213114692  2.768777737  1.038119944  1.976698549  0.782717588
##  [936,]  1.4385936529  1.322774717  0.015515807  0.882537666  0.565505966
##  [937,]  0.6044621875  1.454150020  4.837486642  1.235237251  0.246740026
##  [938,]  0.6424675243  1.093014413  1.101405961  0.555240939  2.149811608
##  [939,]  0.7107859366  1.786123136  0.742420226  1.849893017  1.605305274
##  [940,]  0.7248188781  0.210904091 -0.015945875  1.066310055  0.777047722
##  [941,]  1.2644826188  1.506853200  0.556622657  0.326498940  0.692196830
##  [942,]  1.4857983406  0.764968686  1.323853442  1.263467336  0.443304951
##  [943,]  0.0090491224  0.321722307  2.079597605  0.450114552  1.618866990
##  [944,]  1.0422690829 -0.033276139  1.309362352  0.586265731  0.680570242
##  [945,]  0.4021798725  1.365485613  1.285444882  1.643800009  0.801506440
##  [946,]  0.2301819439  0.463253955  0.410170203  0.924074222  1.748804483
##  [947,]  1.0418809511  2.297518136  1.102962606  1.277603756  2.497220721
##  [948,]  1.3821464314  0.269413658  0.242275914  0.462359285  1.639543840
##  [949,]  1.2838182072  1.993664038 -0.012638752  0.474388464  2.044933780
##  [950,]  0.8502660785  0.338758413  0.802330164  0.613120691  0.927887054
##  [951,]  1.1964912055  1.876050764  0.897471127  0.313610245  3.937532913
##  [952,]  0.3765117980  1.162315065  1.487792086  2.256807441  0.571652432
##  [953,]  0.4876643514  0.781772459  0.698292364  0.707920696 -0.024310853
##  [954,]  0.9053378671  1.038773443  1.174943286  0.826416904  0.938518639
##  [955,]  0.8299497785  0.391238551  1.246066391  0.294353233  0.894318793
##  [956,]  0.7683556253  0.778570557  0.368033048  0.592261897  1.220917017
##  [957,]  0.6078602734  0.736419740  0.764456074  2.023054017  0.887369223
##  [958,]  0.1804438493  3.004026432  1.208654878  0.584428925  0.526545796
##  [959,]  1.1091327665  0.533602031  0.419272786  0.213999194  0.508001243
##  [960,]  2.0379637663  1.756765635  0.466229009  1.760804377  1.254338506
##  [961,]  1.2645054157  0.631814896  1.293433175  0.568534532  0.961909903
##  [962,] -0.0097940260  0.918054881  1.352597380  1.692128545  0.627702044
##  [963,]  3.2328999013  1.382085842  1.230778215  0.441409980  1.342588674
##  [964,]  0.4559427087  0.133405069  0.956609462  0.916229341  0.385883336
##  [965,]  0.8291204229  1.198156529  0.602216025  0.989335827  1.965043732
##  [966,]  1.3924030393  0.624267801  1.687824607  0.679671471  0.873987539
##  [967,]  0.8345209764  1.294866505  0.284222451  1.559821968  1.956058987
##  [968,]  0.3047561798  2.249121383  0.709452702  0.941796457  0.375388615
##  [969,]  0.7115488511  2.174386880  1.313420364  0.849494147  1.980492325
##  [970,]  1.3397812728  1.607947767  0.836141251  0.579921022  0.972109718
##  [971,]  1.3005124709  0.680174210  0.919771175  1.250046870  1.581487752
##  [972,]  1.1361184967  0.264588333  0.287584652  1.446615262  1.145654519
##  [973,]  0.8977994123  0.608882236  0.675902664  0.700752480  0.978587281
##  [974,]  0.2305402631  0.398538632  0.675426584  0.261719746  2.148028123
##  [975,]  0.5766167462  0.284817202  0.520760507  0.208984512  3.869575689
##  [976,]  1.4550858499  0.122226538  0.243587171  0.769625543  0.604347486
##  [977,]  0.4387556308  1.477416502  0.105756181  0.855190469  0.695554996
##  [978,]  1.5833339425  1.845313846  0.850146370  0.691556090  0.770683025
##  [979,]  1.3749061139  1.541154780  3.831982258  1.732537582  1.380990070
##  [980,]  0.5067873716  0.434197885  0.566114697  1.546454471  0.310352318
##  [981,]  0.5831818543  0.676159955  0.523583514 -0.147559327  0.474272996
##  [982,]  0.9383350998  0.927203699  0.389847317  0.832548207  4.443328531
##  [983,]  0.4053273672  2.638485603  0.590127573  1.035634054  1.384822823
##  [984,]  0.8508407420  1.766818062  1.675912990  1.461822507  1.512798202
##  [985,]  0.8259495369  1.497919129  3.888632365  0.849156970  0.627463864
##  [986,]  0.5102302001  0.089099755  1.917017980  0.688806027  0.019194523
##  [987,]  0.4419885695  0.297171601  0.938056009  1.062461352  0.067224923
##  [988,]  0.0528003542  0.510996788  0.488050675  0.799531701  2.007196746
##  [989,]  2.5478685253  0.062152069  1.043761460  4.281392039  0.800580101
##  [990,]  0.5617999695  0.475682328  1.296746000  0.371885098  0.302909175
##  [991,] -0.0587552018  0.606824885  1.019296213  0.366943799  1.359423667
##  [992,]  0.0753971122  0.647206900  1.268956432  1.295225416  1.405413307
##  [993,]  0.6718777226  0.133710114  2.781265260  1.467457680  0.973085238
##  [994,]  0.2688203443  0.279583310  1.319046277  0.723372724  1.029379828
##  [995,]  0.6797800086  2.193864007  0.611698975  0.058411296  0.480969608
##  [996,]  0.4711768366  0.931722397  2.932160662  0.458603182  4.701597535
##  [997,]  1.1344037054  1.193878824  1.081297421  3.098590611  0.352833441
##  [998,]  0.8650671105  0.515233477  1.590938775  1.809711943  4.012287788
##  [999,]  0.6615174877  1.043421630  0.822249590  0.297618364  1.011869133
##                [,11]        [,12]
##    [1,]  0.209518456  2.879874269
##    [2,]  0.882828286  0.644752455
##    [3,]  1.753095484  1.165755146
##    [4,]  2.115494158  2.490619313
##    [5,]  0.364190114  0.363430046
##    [6,]  1.091433076  1.574416426
##    [7,]  0.586266846  0.044066150
##    [8,]  0.778968170  0.707773370
##    [9,]  1.887628978  1.383687810
##   [10,]  1.859707614  2.274569016
##   [11,]  0.762256460  0.708541005
##   [12,]  0.700175239  0.391511060
##   [13,]  1.281904254  0.426904463
##   [14,]  0.637831071  2.288734645
##   [15,]  0.908986985  3.690332696
##   [16,]  0.332655177  0.640156245
##   [17,]  0.462137563  1.473290971
##   [18,]  0.308694602  2.913416339
##   [19,]  0.241247097  1.379882504
##   [20,]  1.328607456  1.636495495
##   [21,]  0.483692747  0.413182405
##   [22,]  1.916510006  0.809417020
##   [23,]  0.983987791  1.886234522
##   [24,]  1.105726419  0.452275920
##   [25,]  0.824285597  0.317317706
##   [26,]  2.284913974  2.316277183
##   [27,]  0.920959112  1.062148726
##   [28,]  0.479421875  0.438420140
##   [29,]  0.485551082  1.605405590
##   [30,]  1.485871686  0.439424964
##   [31,]  2.106433141  0.398518174
##   [32,]  1.062085503  1.382190025
##   [33,]  0.901297994  0.610351263
##   [34,] -0.052028322  2.166051250
##   [35,]  0.819271018  0.665997167
##   [36,]  1.168978578  0.175222522
##   [37,]  0.748112017  0.306976317
##   [38,]  0.194825462  0.611821548
##   [39,]  0.421879020  1.846299573
##   [40,]  1.394091277  2.189132719
##   [41,]  1.134124881  1.389517909
##   [42,]  0.874143980  0.509052334
##   [43,]  0.417406801  0.547011911
##   [44,]  0.567584609  0.814267727
##   [45,]  2.397290779  1.696412796
##   [46,]  0.711959218  0.343608480
##   [47,]  0.513824342  0.373042465
##   [48,]  0.989952446  0.621738941
##   [49,]  0.900126228  1.836750989
##   [50,]  0.380767299  0.571752312
##   [51,]  1.561063140  1.092698840
##   [52,]  0.455706709  0.433050756
##   [53,]  0.894147354  1.615322054
##   [54,]  0.873367651  0.599448001
##   [55,]  1.350247290  0.764374811
##   [56,]  0.957455488  1.532040907
##   [57,]  1.832745794  0.733166408
##   [58,]  0.487427250  1.005999769
##   [59,]  0.912672692  0.560256714
##   [60,]  0.268261105  0.757716972
##   [61,]  1.154191624  0.808558300
##   [62,]  2.796560822  0.883740944
##   [63,]  0.729958688  1.132435050
##   [64,]  0.776410729  0.079313167
##   [65,]  0.396574552  0.620150947
##   [66,]  0.222345786  1.710570557
##   [67,]  1.726648509  1.699508427
##   [68,]  0.360921446  0.787053006
##   [69,] -0.013519647  0.592816347
##   [70,]  0.901055138  0.468260424
##   [71,]  1.256280091  1.216963050
##   [72,]  2.282521614  1.004470627
##   [73,]  0.433735432  0.476531577
##   [74,]  0.596314473  0.987066409
##   [75,]  0.947438250  0.502666397
##   [76,]  0.714475356  0.833530929
##   [77,]  0.769575725  2.212164224
##   [78,]  1.252183429  1.724090468
##   [79,]  1.093361354  0.247494647
##   [80,]  0.194862266  1.337783410
##   [81,]  0.553876113  0.587163048
##   [82,]  1.391058166  0.949079790
##   [83,]  1.761572836  0.492922468
##   [84,]  1.275912252  0.579499638
##   [85,]  0.721417923  0.552787939
##   [86,]  1.666176861  1.166107807
##   [87,]  1.056729467  0.799820639
##   [88,]  1.309739006  0.427916981
##   [89,]  0.602679000  1.650311126
##   [90,]  0.767062975  1.528790964
##   [91,]  0.483734221  0.416935110
##   [92,]  0.904509251  1.887209229
##   [93,]  1.338605352  1.114995272
##   [94,]  0.569790461  0.968951268
##   [95,]  1.235483673  1.459051551
##   [96,]  1.491292312  0.582581722
##   [97,]  1.063383063  2.720445787
##   [98,]  1.232919630  1.779442309
##   [99,]  1.306273513  3.540588217
##  [100,]  0.652359873  1.696944208
##  [101,]  0.297119291  0.943770254
##  [102,]  0.350676626  0.732360379
##  [103,]  0.288858064  0.593908496
##  [104,]  2.113471326  1.197099239
##  [105,]  0.990944654  0.919774248
##  [106,] -0.266694950  1.506245044
##  [107,]  1.390348866  1.765030677
##  [108,]  0.457900621  0.922346775
##  [109,]  0.277284993  0.197965766
##  [110,]  0.572584881  1.657862985
##  [111,]  0.661526476  1.560799319
##  [112,]  1.816242154  0.992209759
##  [113,]  1.857637304  0.986021352
##  [114,]  0.448818615  0.567022010
##  [115,]  1.134674626  1.552575551
##  [116,]  0.926606657  0.251880603
##  [117,]  1.899110140  0.550539338
##  [118,]  0.181757770  0.013785382
##  [119,]  2.269174647  0.904900554
##  [120,]  1.286476370  1.873537537
##  [121,]  0.665294620  0.104527992
##  [122,]  0.593689536  0.402338369
##  [123,]  1.118567510 -0.013442629
##  [124,]  0.882096566  0.265240606
##  [125,]  0.925383498  1.201584254
##  [126,]  1.830000659  0.735447508
##  [127,]  2.281735413  0.920835637
##  [128,]  0.580167441  0.436701415
##  [129,]  0.304423513  1.361964989
##  [130,]  0.464384293  0.948767010
##  [131,]  0.284494648  1.948026520
##  [132,]  0.692742472  0.720621250
##  [133,]  1.408321245  1.109300122
##  [134,]  0.740583829  1.100441824
##  [135,]  1.001824849  0.503253383
##  [136,]  3.263224862  0.193149539
##  [137,]  1.191708613  0.275772169
##  [138,]  0.581599710  0.814841071
##  [139,]  1.175305156  1.103108312
##  [140,]  0.954842593  2.320707068
##  [141,]  0.720326405  0.112039599
##  [142,]  1.591855568  1.004711907
##  [143,]  0.984432228  0.547749767
##  [144,]  0.742110472  2.024160498
##  [145,]  1.320863929  2.633022259
##  [146,]  0.625400747  1.386447515
##  [147,]  1.345732546  1.074003482
##  [148,]  2.158487321  1.418921209
##  [149,]  1.252869432  0.960049746
##  [150,]  0.639622341  0.848218418
##  [151,]  1.929819999  0.552437999
##  [152,]  0.589424579  0.892798306
##  [153,]  0.529721689  1.344872680
##  [154,]  0.285451815  2.001670162
##  [155,]  1.573867305  0.392349632
##  [156,]  0.052487061  0.071717694
##  [157,]  1.919088614  0.186721828
##  [158,]  0.391549277  2.554635551
##  [159,]  2.600067910  1.499154703
##  [160,]  0.293178671  0.053080507
##  [161,]  0.562761863  0.949098520
##  [162,]  1.749344085  2.123416286
##  [163,]  0.462347316  0.748958476
##  [164,]  1.098817291  0.804325985
##  [165,]  0.652098415  0.584090977
##  [166,]  1.235448571  0.505208150
##  [167,]  0.202287347  1.339764780
##  [168,]  0.969669988  1.938507888
##  [169,]  1.227264050  0.204879223
##  [170,]  0.673344484  1.557063432
##  [171,]  1.085841004  0.303279274
##  [172,]  0.579741074  1.051967803
##  [173,]  0.695143392  1.031082110
##  [174,]  1.154943465  0.270500507
##  [175,]  1.110619123  1.179540966
##  [176,]  0.211084630  1.537157267
##  [177,]  0.131442352  0.856421733
##  [178,]  0.760997520  0.543836482
##  [179,]  0.973973879  0.076612386
##  [180,]  0.596442889  1.770104022
##  [181,]  1.425950243  0.423541164
##  [182,]  1.160808524  0.683817826
##  [183,]  0.338497985  1.050145031
##  [184,]  2.101729672  0.606312080
##  [185,]  0.718889025  1.307770480
##  [186,]  0.577431959  2.212655493
##  [187,]  0.772420876  1.381405792
##  [188,]  1.277944650  0.230993006
##  [189,]  0.238630704  0.783100226
##  [190,]  1.697278493  0.353098509
##  [191,]  1.031192459  1.949649447
##  [192,]  1.303370348  0.053389747
##  [193,]  1.106354199  0.913757516
##  [194,]  1.523754911  0.193605528
##  [195,]  0.728950773  0.617002756
##  [196,] -0.056442114  0.392578318
##  [197,]  1.656917350  1.178813079
##  [198,]  1.092456854  0.650287488
##  [199,]  1.192947872  0.734722677
##  [200,]  1.159870333  0.968585868
##  [201,]  1.255345789  0.602169293
##  [202,]  1.012648019  0.797832658
##  [203,]  1.277382447  3.145057371
##  [204,]  1.082813079  1.048776908
##  [205,]  1.197086198  0.304086259
##  [206,]  1.290950924  1.448184854
##  [207,]  1.595806468  0.531183703
##  [208,]  0.280971537  0.872732136
##  [209,]  0.330235248  1.334869765
##  [210,]  0.519954745  1.626893197
##  [211,]  2.100118289  1.617736368
##  [212,]  0.838045580  0.533405381
##  [213,]  1.782728829  1.494625394
##  [214,]  1.427312684  0.519594930
##  [215,]  1.509821624  1.936593079
##  [216,]  0.405097071  1.252160157
##  [217,]  0.928099932  1.114861128
##  [218,]  1.128415730  0.771114271
##  [219,]  1.584282679  0.373073336
##  [220,]  2.425650385  1.267931774
##  [221,]  0.714828946  0.947772470
##  [222,]  0.418010104  1.126707410
##  [223,]  0.721677681  1.807618028
##  [224,]  0.038505471  0.130166139
##  [225,]  0.302696342  0.591313249
##  [226,]  0.409452070  1.468151320
##  [227,]  0.434799173  0.732829399
##  [228,]  0.904815669  2.585626839
##  [229,]  0.995301951  0.762282579
##  [230,]  0.695749404  1.718335040
##  [231,]  0.374515948  0.420924842
##  [232,]  1.813030235  2.341285163
##  [233,]  0.781854055  0.736886535
##  [234,]  1.112476585  0.859214397
##  [235,]  0.428563560  0.338094722
##  [236,]  1.683362348  1.663686475
##  [237,]  0.633998083  0.875809801
##  [238,]  2.148134148  0.733022806
##  [239,]  0.678640271  0.424581994
##  [240,]  1.038369531  0.608092178
##  [241,]  1.057664684  0.654145499
##  [242,]  0.463453580  1.217111082
##  [243,]  2.429062981  0.045846425
##  [244,]  0.087602203  0.440182152
##  [245,]  1.100494332  0.549378796
##  [246,]  1.843674646  2.479042524
##  [247,]  1.932038241  0.538007267
##  [248,]  1.598347805  1.275254602
##  [249,]  0.513342513  0.420817338
##  [250,]  0.758873559  0.793210203
##  [251,]  1.483310570  1.361113143
##  [252,]  1.140234350  0.168050892
##  [253,]  0.711063793  0.308375880
##  [254,]  0.001217329  0.365584838
##  [255,]  0.490534612  3.087588223
##  [256,]  0.947527354 -0.026392673
##  [257,]  0.463069075  0.497347987
##  [258,]  2.172097055  0.660008415
##  [259,]  0.109504970  3.131384513
##  [260,]  0.002934802  1.168002133
##  [261,]  1.823848317  0.415808699
##  [262,]  0.329526779  1.628221927
##  [263,]  0.099175367  1.579136741
##  [264,]  1.134476050  0.417419477
##  [265,]  0.964609845  0.608021892
##  [266,]  0.497216872  0.481880407
##  [267,]  0.702696995  0.494076267
##  [268,]  0.257920743  1.597490959
##  [269,]  0.470641228  0.062284212
##  [270,]  0.476895138  0.607018024
##  [271,]  1.198117314  0.765407137
##  [272,]  0.664083941  0.825573822
##  [273,]  0.278359150  1.110991808
##  [274,]  0.203450488  0.443191722
##  [275,]  1.498979142  0.416205041
##  [276,]  1.303623383  0.429196594
##  [277,]  1.368324286  0.440646777
##  [278,]  0.830356643  0.147865663
##  [279,]  0.997991579  1.032372505
##  [280,]  0.127742054  1.155564293
##  [281,]  0.686680269  1.896468977
##  [282,]  1.412152976  0.562309503
##  [283,]  0.648609404  0.998760098
##  [284,]  1.422267297  0.567964861
##  [285,]  1.366556256  1.359552769
##  [286,]  0.345034196  0.203262014
##  [287,]  0.547236589  0.932024331
##  [288,]  1.041994831  2.180187945
##  [289,]  0.427603863  0.867432799
##  [290,]  0.038440322  1.034085931
##  [291,]  2.360938874  0.560351130
##  [292,]  1.096439956  2.234926494
##  [293,]  0.667520462  0.850874950
##  [294,]  1.102843928  0.623369071
##  [295,]  0.245377369  1.541739199
##  [296,]  0.211316421  0.767341766
##  [297,]  0.777167154  0.497811139
##  [298,]  0.330893887 -0.131124330
##  [299,]  3.238285187  0.752720485
##  [300,]  2.376894955  0.305929736
##  [301,]  2.538409829  0.986135038
##  [302,]  2.373029500  0.826706048
##  [303,]  1.297746865  0.269930318
##  [304,]  0.401587270  0.059353669
##  [305,]  0.536158401  0.866341425
##  [306,]  0.775273769  1.592572072
##  [307,]  0.104648972  0.289488515
##  [308,]  0.979624875  0.884825339
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##  [682,]  1.203463815  0.700274681
##  [683,]  0.606494930  0.962104973
##  [684,]  0.036836435  0.613350481
##  [685,]  0.916256840  0.253435004
##  [686,]  2.394745597  1.193290051
##  [687,]  1.063963690  0.822789303
##  [688,]  0.184372333  1.184572396
##  [689,]  0.385047740  1.287679986
##  [690,]  2.266484834  0.089472212
##  [691,]  4.739018782  1.130987198
##  [692,]  0.377394644  0.614339382
##  [693,]  1.163766203  0.553313126
##  [694,]  0.591669420  0.834717892
##  [695,]  0.844726826  0.698669819
##  [696,]  0.290955405  2.548558759
##  [697,]  1.189749406  0.408856897
##  [698,]  0.622349439  0.426479321
##  [699,]  1.081910531  0.859027855
##  [700,]  1.960761555  0.258402702
##  [701,]  0.421414542  0.366481273
##  [702,]  0.379997029  1.021830014
##  [703,]  0.689823559  0.844443878
##  [704,]  0.516144830  1.242944127
##  [705,]  0.429214940  2.079870770
##  [706,]  0.651843789  0.643498176
##  [707,]  0.130665615  0.305895147
##  [708,]  0.931863557  0.148864896
##  [709,]  0.705952228  3.753734867
##  [710,]  0.787988026  0.449773812
##  [711,] -0.092650435  1.622756364
##  [712,]  0.423066873  1.210459830
##  [713,]  0.176813539  0.515858396
##  [714,]  1.823117681  1.800476101
##  [715,]  0.658496446  1.312194880
##  [716,]  0.357458130  2.284156515
##  [717,]  3.825015632  0.501910570
##  [718,]  2.682318783  0.441920610
##  [719,]  0.617635263  0.613844922
##  [720,]  0.838754557  0.429821527
##  [721,]  0.939916068  0.908934101
##  [722,]  0.547508769  1.700992396
##  [723,]  0.653349047  0.477717384
##  [724,]  0.093994956  0.820487806
##  [725,]  1.052614757  0.212938307
##  [726,]  0.950432850  1.567225075
##  [727,]  0.457413907  0.386388114
##  [728,]  1.629616479  1.229037469
##  [729,]  0.627846481  1.935563724
##  [730,]  1.409005640  1.014544717
##  [731,]  0.153604885  1.004482583
##  [732,]  1.040959814  1.687854840
##  [733,]  1.280143626  1.697925298
##  [734,]  1.620785521  0.187308772
##  [735,]  1.663749513  1.308567722
##  [736,]  1.005962845  1.065556953
##  [737,]  0.434122529  2.026511038
##  [738,]  0.904222889  0.580309453
##  [739,]  0.336378624  0.119863304
##  [740,]  0.057909537  1.213309409
##  [741,]  0.943154139  0.523643427
##  [742,]  0.871929549  2.076492765
##  [743,]  0.173108877  1.018863024
##  [744,]  0.355124583  0.274022632
##  [745,]  0.905011759  1.587366575
##  [746,]  1.571175374  1.414877300
##  [747,]  0.655873011  0.268036972
##  [748,]  0.934459572  1.256009489
##  [749,]  1.300542222  0.679802907
##  [750,]  1.118778704  0.230281237
##  [751,]  1.186339827  1.884239564
##  [752,]  0.958851346  0.498838657
##  [753,]  0.588578338  0.995544613
##  [754,]  0.192945532  0.343091968
##  [755,]  0.121725102  0.358112051
##  [756,]  0.130345623  0.719478648
##  [757,]  0.030222656  1.093562976
##  [758,]  1.324590437  1.554797909
##  [759,]  0.866944717  0.583670753
##  [760,]  0.520085827  1.588841330
##  [761,]  3.665451017  0.360326886
##  [762,]  0.313866567  0.180822336
##  [763,]  0.613986186  0.532271239
##  [764,]  0.612250619  1.418105405
##  [765,]  0.545357708  0.739616443
##  [766,]  5.265615179  0.496734653
##  [767,]  0.569129697  0.513388641
##  [768,]  1.165893684  1.090085485
##  [769,]  0.298470837  0.720891145
##  [770,]  1.835993803  0.618887286
##  [771,]  0.357464999  0.653410614
##  [772,]  1.236981758  1.174890750
##  [773,]  3.221866200  0.710795474
##  [774,]  1.532152537  2.099271925
##  [775,]  0.272519288  1.171454959
##  [776,]  0.657904766  0.190480100
##  [777,]  1.490675248  0.360027959
##  [778,]  0.559131878  0.722527828
##  [779,]  1.910385994  1.276351552
##  [780,]  1.268721409  1.128199292
##  [781,]  0.840797768  1.460765003
##  [782,]  0.509637670  1.542108581
##  [783,]  1.946232670  0.646227201
##  [784,]  2.662654667  0.488690937
##  [785,]  2.314572242  0.462068655
##  [786,]  2.460201512  0.527555270
##  [787,]  0.938634796  0.514515216
##  [788,]  1.274493224  0.199390134
##  [789,]  0.965643369  0.511066896
##  [790,]  0.723106151  1.292675327
##  [791,]  0.601874853  1.494998068
##  [792,]  0.485518490  0.854425005
##  [793,]  1.031038175  0.891830111
##  [794,]  0.579356776  0.411799130
##  [795,]  0.498745396  0.966114962
##  [796,]  1.441475662  0.911639254
##  [797,]  1.041678759  0.863510073
##  [798,]  0.923497243  1.724701537
##  [799,]  1.256143283  0.588728496
##  [800,]  0.344979340  3.627891756
##  [801,]  0.719582699  0.633363091
##  [802,]  0.513713394  1.130623855
##  [803,]  1.015066685  0.499789938
##  [804,]  0.508929932  1.844337019
##  [805,]  0.405642546  1.351853065
##  [806,] -0.072933615  2.469186914
##  [807,]  1.858457028  1.054250799
##  [808,]  0.894433419  1.589274154
##  [809,]  1.253274215  0.717658054
##  [810,]  1.027980689  0.824428978
##  [811,]  2.457963664  1.526672748
##  [812,]  3.453410734  0.598283357
##  [813,]  0.601544198  1.106631559
##  [814,]  1.330145049  2.458139208
##  [815,]  0.657134331  0.589421511
##  [816,]  1.543285434  0.956707692
##  [817,]  1.790945546  1.619933758
##  [818,]  0.446828661  0.508080076
##  [819,]  1.925963131  3.402076346
##  [820,]  0.547964997  1.348139930
##  [821,]  0.194203763  0.301922711
##  [822,]  0.046143699  1.432644375
##  [823,]  0.619767355  0.737501779
##  [824,]  0.169656297  0.979627674
##  [825,]  0.213212393  0.435876035
##  [826,]  0.795488899  1.308051661
##  [827,]  0.565133912  0.261483356
##  [828,]  0.585787736  0.385713995
##  [829,]  2.244619257  1.041620560
##  [830,]  0.621450752  0.696028944
##  [831,]  1.440441362  0.536254809
##  [832,]  1.301582624  0.686753578
##  [833,]  1.019520714  0.442833871
##  [834,]  0.613420791  1.964403916
##  [835,]  0.527923358  1.179490070
##  [836,] -0.148892983  2.247062672
##  [837,]  0.140940284  0.708043041
##  [838,]  0.451402340  1.469388200
##  [839,]  0.102922522  0.578212420
##  [840,]  0.674611375  0.078958926
##  [841,]  1.991470240  1.814318615
##  [842,]  4.005892922  0.446693831
##  [843,]  1.333874891  1.354381592
##  [844,]  0.546592916  0.699300190
##  [845,]  0.709229165  0.435869022
##  [846,]  2.332431216  0.316761553
##  [847,]  2.140610280  1.476065574
##  [848,]  0.789023494  1.821330074
##  [849,]  0.690295479  0.999123262
##  [850,]  0.823208578  1.103939797
##  [851,]  1.429630546  0.915316213
##  [852,]  0.776816537  1.164670478
##  [853,]  2.402339977  1.300763211
##  [854,]  1.207512049  2.605477184
##  [855,]  0.354014386  1.010210276
##  [856,]  0.514410956  0.781990125
##  [857,]  0.210855994  1.666311915
##  [858,]  0.433536336  0.051668382
##  [859,]  0.471793455  1.904869927
##  [860,]  0.025406953  0.758656880
##  [861,]  0.705570185  1.228151673
##  [862,]  0.976182405  0.199185092
##  [863,]  0.565607104  1.503482550
##  [864,]  0.244929639  0.706622847
##  [865,]  0.796780595  0.292178210
##  [866,]  1.668887856  0.385011344
##  [867,]  1.358353503  0.934025096
##  [868,]  1.414826422  0.962971027
##  [869,]  0.992212431  1.796442649
##  [870,] -0.004657223  1.037687509
##  [871,]  2.289349166  3.058566605
##  [872,]  0.912435480  1.133337660
##  [873,]  1.507626830  0.495535192
##  [874,]  0.975597014  0.792997118
##  [875,]  0.343801882  0.441289135
##  [876,]  1.470825928  0.853401892
##  [877,]  1.503357511  0.894713672
##  [878,]  2.858147530  1.577977647
##  [879,]  1.353833399  0.740129282
##  [880,]  0.889094076  0.763670768
##  [881,]  0.511204724  0.540320537
##  [882,]  0.488919059  0.690013593
##  [883,]  0.856875585  1.053890885
##  [884,]  0.730107910  1.322987313
##  [885,]  1.018391363  0.279135618
##  [886,]  0.491145788  0.665242505
##  [887,]  0.587556978  0.523977202
##  [888,]  2.443823241  1.198118629
##  [889,]  0.263499743  0.403983388
##  [890,]  0.334388301  0.755049895
##  [891,]  0.122986363  0.143743189
##  [892,]  1.216378439 -0.015478455
##  [893,]  1.114307843  0.594655057
##  [894,]  1.453474531  0.302389665
##  [895,]  2.114180158  0.544790454
##  [896,]  3.472833242  0.979227776
##  [897,]  1.374476918  1.678486825
##  [898,]  1.145568205  0.663628670
##  [899,]  0.792973257  0.448674450
##  [900,]  1.842539814 -0.091609036
##  [901,]  0.603608815  0.463213246
##  [902,]  1.260772097  0.400065256
##  [903,]  0.280864392  1.077163521
##  [904,]  2.977643486  1.292691548
##  [905,]  1.507477600  0.376019574
##  [906,]  0.073648508  0.597157413
##  [907,]  0.805534010  2.198076595
##  [908,]  0.822293379  0.819089958
##  [909,]  0.401275495  1.071688638
##  [910,]  0.292604294  0.584921952
##  [911,]  2.183461384  0.356128775
##  [912,]  1.132094998  0.768459174
##  [913,]  0.737442898  0.669880956
##  [914,]  1.359343716  1.311450751
##  [915,]  1.433077113  1.286534926
##  [916,]  0.243984125  1.074631574
##  [917,]  1.573701717  0.172892590
##  [918,]  1.040469231  0.680792608
##  [919,]  2.175618189  2.092032102
##  [920,]  1.883664184  0.526165792
##  [921,]  0.759234526  1.458585932
##  [922,]  1.073250436  0.506595501
##  [923,]  0.915492179  0.262445623
##  [924,]  0.267044391  1.238772896
##  [925,]  0.993139577  0.317424967
##  [926,]  0.285973100  1.634152317
##  [927,]  0.220217805  0.133700778
##  [928,]  1.130601463  0.528247381
##  [929,]  0.819980815  1.069619177
##  [930,]  0.456838107  1.142211965
##  [931,]  1.279308882  1.180452322
##  [932,]  0.202720128  0.875402896
##  [933,]  1.704693912  0.273138620
##  [934,]  1.158667038  0.273345132
##  [935,]  1.841131915  0.527824894
##  [936,]  1.034772261  1.097550868
##  [937,]  1.358218437  0.287118907
##  [938,]  0.856674797  1.460173151
##  [939,]  1.364009709  2.480036397
##  [940,]  0.798838238  0.391978203
##  [941,]  1.929733051  1.016986335
##  [942,]  1.562844776  1.129780161
##  [943,]  1.262083999  1.579317632
##  [944,]  1.254683338  0.357480781
##  [945,]  1.164413762  2.310925434
##  [946,]  1.865713738 -0.088764945
##  [947,]  0.319366720  1.461612914
##  [948,]  0.997362645  1.301539424
##  [949,]  0.422148977  0.525506589
##  [950,]  1.469132846  1.131928732
##  [951,]  0.760304677  1.112038868
##  [952,]  2.433821066  0.078777643
##  [953,]  1.371351368  0.405600538
##  [954,]  1.106531482  1.000872786
##  [955,]  0.255449380  0.177782934
##  [956,]  1.005235131  1.995133219
##  [957,]  0.108478357  0.379906867
##  [958,]  1.708280748  1.809313388
##  [959,]  1.301002101  2.187265696
##  [960,]  0.917394370  0.931117871
##  [961,]  0.159759546  1.316662828
##  [962,]  0.229038795  0.468343557
##  [963,]  0.787109517  0.139299685
##  [964,]  0.104651130  0.034438573
##  [965,]  1.367041211  2.491216203
##  [966,]  0.308434146  0.659628497
##  [967,]  0.926527451  1.250044568
##  [968,]  0.651346821  1.120429335
##  [969,]  0.608853370  1.135222853
##  [970,]  0.840105101  1.119485529
##  [971,]  1.979794863  0.868885541
##  [972,]  0.529531604  0.796266732
##  [973,]  1.188591087  0.503317672
##  [974,]  0.215607012  0.654324785
##  [975,]  0.475073077  1.901282651
##  [976,]  0.508168503  0.190942196
##  [977,]  1.085135505  0.349670582
##  [978,]  2.029647658  1.401630255
##  [979,]  0.127483163  0.208581497
##  [980,]  1.878274963  1.347008594
##  [981,]  0.692305763  0.736566935
##  [982,]  1.470200164  1.769319129
##  [983,]  0.387185437  1.893553633
##  [984,]  1.031871168  3.124225172
##  [985,]  2.906210045  1.121383485
##  [986,]  0.346935018  0.776083271
##  [987,]  1.068789728  0.499599920
##  [988,]  2.441558611  1.403159136
##  [989,]  1.617549955  0.684828497
##  [990,]  0.571907917  0.647061419
##  [991,]  1.922870880  1.226333612
##  [992,]  1.964211572  0.319326597
##  [993,]  1.007545563  1.640456054
##  [994,]  0.822789059  1.386321371
##  [995,]  1.250619171  1.697889887
##  [996,]  0.070102314  1.730792977
##  [997,]  0.035694890  1.259148551
##  [998,]  1.455178476  0.724351613
##  [999,]  0.754631167  0.816081018
## 
## $model.matrix
##    (Intercept) avlength avcondition   T_av O2_sat_av    Con_av COD_av NH4._av
## 1            1 46.26316   0.7032430 11.114    81.286  740.7140 13.333   0.158
## 2            1 38.30000   0.6196317 10.440    65.400  609.6000  1.400   0.774
## 3            1 47.20000   0.7209293 12.858    75.333  434.7500 25.917   2.251
## 4            1 33.60000   0.7279046 13.086    72.857  949.0000 25.000   5.000
## 5            1 33.30769   0.6910252 11.750    96.833  896.1670 14.000   0.303
## 6            1 35.05263   0.7161573 13.557    84.571  340.7140 29.000   0.252
## 7            1 35.53333   0.7532778 11.750    88.417  716.3330 16.583   0.393
## 9            1 41.66667   0.8590551 12.008    87.000  800.3330 21.917   0.468
## 11           1 39.89474   0.6943120 13.550    63.167  527.6670 45.500   3.233
## 12           1 32.90909   0.6629259 14.957    65.857 1089.8570 50.500   5.365
## 13           1 39.88235   0.7324076 14.486    90.429  771.7143 11.333   0.668
## 14           1 38.42857   0.7578120 11.983    77.667  472.3330 37.167   2.367
## 15           1 34.23077   0.7642545 11.577    85.308  591.4620 24.667   0.260
## 16           1 43.61111   0.6500428 12.443    87.857  462.5710 37.167   0.210
## 17           1 40.16667   0.7486984 11.425    73.250  470.3330 20.000   2.589
## 18           1 37.43750   0.9549238 16.214    61.000  422.4290 35.833   2.417
## 19           1 41.47059   0.6295888  9.317    94.900  812.8330  7.500   0.103
## 20           1 28.00000   0.7382850 12.957    85.571  851.2860 15.833   0.170
## 21           1 37.84211   0.7477438 15.000    85.333  673.1670 19.500   0.635
## 22           1 42.00000   0.6865490 10.475    73.833  255.8330 24.727   0.527
## 23           1 36.50000   0.7425513 10.050    80.000  138.6670 37.167   0.290
## 24           1 43.58333   0.8243429 11.773    66.091  593.0910 34.727   0.806
## 26           1 31.72222   0.8809334 12.167    80.333  897.4170 16.417   0.409
## 28           1 40.31579   0.7644699 13.433    99.667  801.0000 20.909   0.354
## 29           1 39.25000   0.8383703 14.133    87.667  669.6670 14.000   0.227
## 30           1 42.37500   0.7907723 13.542    48.833  542.4170 42.333   2.261
## 31           1 42.00000   0.8148913 12.867    70.333  447.3330 29.333   0.680
## 32           1 38.87500   0.6351264 13.186    91.857  617.5710 19.333   0.362
## 33           1 37.31579   0.7512399 15.233    84.000  539.3330 13.667   0.325
## 34           1 38.73684   0.6217274 12.050    92.583  659.8330 14.750   0.336
## 35           1 37.85714   0.8194431 11.175    91.375  687.3750 26.000   0.395
## 36           1 32.88889   0.6862546 13.700    88.833  755.5000 26.167   1.260
## 38           1 34.65000   0.6616806 13.633    77.500  667.0000 20.333   0.695
## 39           1 33.25000   0.7554143 11.333    43.750  848.3330 35.750   2.542
## 40           1 36.75000   0.6487052 12.900    71.400  635.0000 16.400   2.208
## 41           1 36.35000   0.8265861 15.100    94.000  716.3330 15.167   0.165
## 42           1 35.15789   0.7600249 13.786    89.571  705.7140 18.167   0.880
##        Nt_av pool_riffle1 meander1   netcen    updist
## 1   8.917000           -1       -1 65212.97 67745.125
## 2   4.780000            1        1 50877.11 52437.119
## 3   8.925000            1       -1 38651.53 32574.449
## 4   9.067000           -1       -1 63911.70 65226.644
## 5   5.167000            1       -1 64168.17 67952.655
## 6   1.617000            1        1 45262.05 45780.074
## 7   2.775000            1        1 72386.11 76509.324
## 9   6.083000            1       -1 47724.46 49932.683
## 11  5.750000            1        1 49875.30 52217.733
## 12 16.100000           -1       -1 61880.37 26695.488
## 13  6.533000            1        1 60618.70 25511.682
## 14  7.000000            1        1 56056.62 15064.968
## 15  2.608000           -1        1 63687.75 67470.687
## 16  1.730000           -1       -1 68548.11 72561.660
## 17 10.617000           -1       -1 45271.82 39387.485
## 18  5.450000            1       -1 44142.92 15837.759
## 19  5.358361           -1       -1 64632.42 67396.486
## 20  4.583000            1       -1 72865.43 76898.411
## 21  5.067000           -1        1 58440.64 21751.460
## 22  2.164000            1        1 47879.02 44196.470
## 23  1.372000            1        1 53511.26 49989.625
## 24  4.891000            1       -1 37413.39 35027.425
## 26  5.242000            1        1 59347.24 62693.461
## 28  4.636000            1       -1 45740.16 46890.918
## 29  7.550000           -1       -1 73590.70 39137.994
## 30  3.317000            1        1 45131.08 29684.138
## 31  3.283000            1        1 43713.21  2368.891
## 32  4.767000           -1       -1 55885.32 18797.654
## 33  3.683000            1        1 63398.00 26850.462
## 34  8.050000           -1        1 65158.98 30465.362
## 35  4.317000           -1       -1 59901.23 62281.614
## 36  5.567000           -1        1 63856.37 66416.408
## 38  7.033000            1        1 53189.12 16286.394
## 39  5.017000            1        1 63663.04 23736.389
## 40  3.243000            1        1 60384.21 20784.664
## 41  2.550000           -1       -1 60481.19 20943.659
## 42  3.450000            1        1 64836.74 25423.656
## 
## $terms
## spe.hel_bray ~ avlength + avcondition + T_av + O2_sat_av + Con_av + 
##     COD_av + NH4._av + Nt_av + pool_riffle + meander + netcen + 
##     updist
## attr(,"variables")
## list(spe.hel_bray, avlength, avcondition, T_av, O2_sat_av, Con_av, 
##     COD_av, NH4._av, Nt_av, pool_riffle, meander, netcen, updist)
## attr(,"factors")
##              avlength avcondition T_av O2_sat_av Con_av COD_av NH4._av Nt_av
## spe.hel_bray        0           0    0         0      0      0       0     0
## avlength            1           0    0         0      0      0       0     0
## avcondition         0           1    0         0      0      0       0     0
## T_av                0           0    1         0      0      0       0     0
## O2_sat_av           0           0    0         1      0      0       0     0
## Con_av              0           0    0         0      1      0       0     0
## COD_av              0           0    0         0      0      1       0     0
## NH4._av             0           0    0         0      0      0       1     0
## Nt_av               0           0    0         0      0      0       0     1
## pool_riffle         0           0    0         0      0      0       0     0
## meander             0           0    0         0      0      0       0     0
## netcen              0           0    0         0      0      0       0     0
## updist              0           0    0         0      0      0       0     0
##              pool_riffle meander netcen updist
## spe.hel_bray           0       0      0      0
## avlength               0       0      0      0
## avcondition            0       0      0      0
## T_av                   0       0      0      0
## O2_sat_av              0       0      0      0
## Con_av                 0       0      0      0
## COD_av                 0       0      0      0
## NH4._av                0       0      0      0
## Nt_av                  0       0      0      0
## pool_riffle            1       0      0      0
## meander                0       1      0      0
## netcen                 0       0      1      0
## updist                 0       0      0      1
## attr(,"term.labels")
##  [1] "avlength"    "avcondition" "T_av"        "O2_sat_av"   "Con_av"     
##  [6] "COD_av"      "NH4._av"     "Nt_av"       "pool_riffle" "meander"    
## [11] "netcen"      "updist"     
## attr(,"order")
##  [1] 1 1 1 1 1 1 1 1 1 1 1 1
## attr(,"intercept")
## [1] 1
## attr(,"response")
## [1] 1
## attr(,".Environment")
## <environment: R_GlobalEnv>
## 
## attr(,"class")
## [1] "adonis"
# environmental variables
env_select <- environment2[,c("T_av", "O2_sat_av", "Con_av", "COD_av", "NH4._av", "Nt_av", "pool_riffle", "meander", "netcen", "updist")]
env_select$pool_riffle <- as.numeric(env_select$pool_riffle)
env_select$meander <- as.numeric(env_select$meander)

pca <- prcomp(env_select, scale.=T)
summary(pca)
## Importance of components:
##                           PC1    PC2    PC3    PC4     PC5     PC6     PC7
## Standard deviation     1.7124 1.5545 1.1221 1.0140 0.88807 0.79463 0.56647
## Proportion of Variance 0.2933 0.2416 0.1259 0.1028 0.07887 0.06314 0.03209
## Cumulative Proportion  0.2933 0.5349 0.6608 0.7636 0.84248 0.90563 0.93771
##                            PC8     PC9    PC10
## Standard deviation     0.50483 0.46939 0.38429
## Proportion of Variance 0.02549 0.02203 0.01477
## Cumulative Proportion  0.96320 0.98523 1.00000
plot(pca)

biplot(pca)

# Assess the effect of environmental variables on parasite component community dissimilarities using distance based RDA
spe.rda <- dbrda(spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
anova(spe.rda)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     8   1.1664 1.2909  0.166
## Residual 28   3.1624
RsquareAdj(spe.rda)$adj.r.squared
## [1] 0.06072755
mod0 <- dbrda(spe.hel_bray ~ 1, env_select[,-c(9:10)])  # Model with intercept only  #edit_PH
mod1 <- dbrda(spe.hel_bray ~ ., env_select[,-c(9:10)])  # Model with all explanatory variables  #edit_PH
step.res <- ordiR2step(mod0, mod1, direction = "both",perm.max = 200)
## Step: R2.adj= 0 
## Call: spe.hel_bray ~ 1 
##  
##                  R2.adjusted
## <All variables>  0.060727547
## + T_av           0.036398792
## + NH4._av        0.020208612
## + meander        0.018502880
## + O2_sat_av      0.004277611
## + Con_av         0.001872668
## + pool_riffle    0.001742860
## <none>           0.000000000
## + Nt_av         -0.002060170
## + COD_av        -0.017968936
## 
##        Df    AIC      F Pr(>F)  
## + T_av  1 54.788 2.3599   0.07 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
step.res$anova  # Summary table
## NULL
plot(spe.rda, scaling = 1) # it is for technical reasons not possible to plot both site and species scores

summary(spe.rda)
## 
## Call:
## dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av +      NH4._av + Nt_av + pool_riffle + meander, data = env_select) 
## 
## Partitioning of squared Bray distance:
##               Inertia Proportion
## Total           4.329     1.0000
## Constrained     1.166     0.2695
## Unconstrained   3.162     0.7305
## 
## Eigenvalues, and their contribution to the squared Bray distance 
## 
## Importance of components:
##                       dbRDA1 dbRDA2  dbRDA3  dbRDA4   dbRDA5    dbRDA6
## Eigenvalue            0.5740 0.3372 0.17566 0.09415 0.042525 0.0020670
## Proportion Explained  0.1326 0.0779 0.04058 0.02175 0.009824 0.0004775
## Cumulative Proportion     NA     NA      NA      NA       NA        NA
##                         idbRDA1  idbRDA2   MDS1   MDS2   MDS3    MDS4    MDS5
## Eigenvalue            -0.014797 -0.04441 1.3249 0.8027 0.4680 0.31323 0.29121
## Proportion Explained   0.003418  0.01026 0.3061 0.1854 0.1081 0.07236 0.06727
## Cumulative Proportion        NA       NA     NA     NA     NA      NA      NA
##                          MDS6    MDS7    MDS8    MDS9   MDS10   MDS11   MDS12
## Eigenvalue            0.13644 0.11438 0.08987 0.07065 0.06425 0.02766 0.01576
## Proportion Explained  0.03152 0.02642 0.02076 0.01632 0.01484 0.00639 0.00364
## Cumulative Proportion      NA      NA      NA      NA      NA      NA      NA
##                          MDS13     MDS14      iMDS1     iMDS2    iMDS3
## Eigenvalue            0.011872 2.725e-04 -0.0020314 -0.007356 -0.01078
## Proportion Explained  0.002743 6.295e-05  0.0004693  0.001699  0.00249
## Cumulative Proportion       NA        NA         NA        NA       NA
##                           iMDS4    iMDS5     iMDS6     iMDS7    iMDS8     iMDS9
## Eigenvalue            -0.014744 -0.01935 -0.022495 -0.029849 -0.03342 -0.041489
## Proportion Explained   0.003406  0.00447  0.005197  0.006895  0.00772  0.009584
## Cumulative Proportion        NA       NA        NA        NA       NA        NA
##                         iMDS10   iMDS11   iMDS12   iMDS13   iMDS14
## Eigenvalue            -0.05984 -0.06439 -0.06995 -0.09116 -0.10203
## Proportion Explained   0.01382  0.01487  0.01616  0.02106  0.02357
## Cumulative Proportion       NA       NA       NA       NA       NA
## 
## Accumulated constrained eigenvalues
## Importance of components:
##                       dbRDA1 dbRDA2 dbRDA3  dbRDA4  dbRDA5   dbRDA6  idbRDA1
## Eigenvalue            0.5740 0.3372 0.1757 0.09415 0.04252 0.002067 -0.01480
## Proportion Explained  0.4921 0.2891 0.1506 0.08072 0.03646 0.001772  0.01269
## Cumulative Proportion     NA     NA     NA      NA      NA       NA       NA
##                        idbRDA2
## Eigenvalue            -0.04441
## Proportion Explained   0.03807
## Cumulative Proportion       NA
## 
## Scaling 2 for species and site scores
## * Species are scaled proportional to eigenvalues
## * Sites are unscaled: weighted dispersion equal on all dimensions
## * General scaling constant of scores:  3.533199 
## 
## 
## Site scores (weighted sums of species scores)
## 
##      dbRDA1   dbRDA2   dbRDA3    dbRDA4   dbRDA5   dbRDA6
## 1  -0.07530 -0.62580 -0.63602 -2.643196 -0.34427 -23.8946
## 2   0.87242  0.77832 -0.32068  2.074749 -0.25800  41.3754
## 3  -0.81094  1.29200 -0.57735 -0.708420 -2.35800  -5.0035
## 4  -0.97450  0.91051  1.79849 -2.192492 -1.99248  -4.7134
## 5  -0.25889  0.74559 -1.30995 -1.418227  0.33185 -21.9720
## 6   0.41640  1.01888 -0.34551 -2.318324  1.61924 -24.8949
## 7  -0.98286 -0.67495  0.62017  1.174218  1.55155  -0.8974
## 8   0.93807  0.62635 -3.10878 -0.765073  2.41981  -3.0764
## 9  -0.62816 -0.77245 -1.30540  1.806170  1.30543 -41.2679
## 10 -1.03727 -0.50089  0.62572  0.369727  1.00378   4.7819
## 11  1.10743 -0.99448 -0.66515 -0.071830  0.83402 -14.8528
## 12  0.61624  0.76828  0.87110  0.357836  0.12125  38.2552
## 13 -0.96088 -0.72453  0.47977  1.569869  1.43399  -6.8692
## 14  1.41128  2.03453 -1.67256  0.776255  0.27648  29.9435
## 15 -1.00448 -0.59302  0.65010  0.833950  1.44643   3.4902
## 16  1.26382  0.81623  3.19230  1.380128  1.12523 -10.4959
## 17 -0.92726 -0.73637  0.33774  1.892276  1.07787  -8.2400
## 18 -1.04523 -1.01280 -0.59052  2.897871  0.35870 -14.2865
## 19  0.89987 -1.54255 -0.54435  1.738188 -2.61939  32.8867
## 20 -0.14608 -0.34079  0.78630  1.316880  1.70249  -9.1246
## 21 -1.30124 -1.46318 -1.27370  3.739798  0.91928 -16.7232
## 22 -0.07485  1.73636  0.30728 -1.760677 -0.46041   6.1504
## 23 -0.18008 -0.64105  0.55428 -1.310793 -0.82437  -3.6579
## 24  0.53054  0.08088  1.31623 -3.529128 -1.96164  41.6937
## 25 -0.50901 -0.82222 -1.26480  2.167458 -6.71178 -22.4535
## 26  0.54874  0.92050  1.12409  0.009258  0.07714  34.0773
## 27  1.25804 -0.69768  2.37255 -1.697654 -3.24936 -16.2349
## 28 -0.86554  0.32492 -0.68347  0.704689 -0.16329  13.0277
## 29  1.82276  0.98120  0.33891 -1.852448  4.33581  -8.6587
## 30  0.72974 -0.59907 -1.00943 -0.201449  1.77124  -4.5186
## 31 -1.02904  0.19515  1.05102 -1.468951 -1.36610  23.1359
## 32 -0.13877 -0.06050 -0.19569 -1.899083 -1.10403 -31.4856
## 33  1.01209 -0.59332  2.58400 -0.318337 -1.43566  39.0635
## 34 -0.39319 -1.79743  0.20497 -0.362972 -0.59693 -19.8004
## 35 -0.89506  1.46497 -0.05622 -1.876722 -1.86120   3.5844
## 36  0.87386  1.17335 -3.50567  1.196922  1.51036  -9.4970
## 37 -0.06267 -0.67495 -0.14975  0.389535  2.08495  11.1529
## 
## 
## Site constraints (linear combinations of constraining variables)
## 
##      dbRDA1   dbRDA2   dbRDA3   dbRDA4    dbRDA5   dbRDA6
## 1  -0.16605 -0.69736 -0.45052  0.39949 -1.140870  0.26766
## 2  -0.07683 -0.33692  0.61638  0.50606 -0.381728  1.66676
## 3  -0.10071  0.76299  0.51759  0.02910  0.003366 -0.26259
## 4  -1.55548  0.90013  0.66933 -0.51241 -0.415318 -0.13093
## 5  -0.41914  0.27994 -0.66104 -1.10909  0.384267  0.50060
## 6   0.63090  0.30135 -0.07724  0.37780  0.857007 -0.33310
## 7  -0.15252 -0.25647 -0.20458 -0.38652  0.792931  0.48033
## 8  -0.14874  0.12938 -0.39866 -0.78891  0.083814  0.27677
## 9  -0.14359  0.11628  0.95439 -0.04629  0.609992 -0.64671
## 10 -0.74154 -0.65088  0.87072 -1.17151 -0.875610 -1.73263
## 11  0.77571 -0.48314  0.02321 -0.76003  0.259283 -0.01494
## 12 -0.44387 -0.28442  0.54938 -0.01813  1.062736 -0.71676
## 13 -0.25608 -0.61494 -0.47847  0.74269  0.180828 -0.14346
## 14 -0.23636  0.67472 -0.87185  0.72759  0.046993 -0.61306
## 15 -0.75508  0.19781  0.41035  0.89449 -0.744271 -0.25040
## 16  0.97946  1.50039  0.74911  0.12808 -0.657115 -0.30363
## 17 -1.19679 -0.18091 -0.90174  0.16093 -0.229189  0.70454
## 18  0.23197  0.39183 -0.42932 -0.82808 -0.242760  0.64991
## 19  0.80868 -0.55920 -0.22435  0.32426 -0.445610 -0.51746
## 20 -0.19206  0.12003  0.24728  0.99541  0.747110  0.40576
## 21 -0.38477  0.09371 -0.03632  1.07969  1.383306 -0.25819
## 22  0.02352  0.34014  0.07462  0.03662 -0.352806  0.35626
## 23  0.18716 -0.91860 -0.02126 -0.69548  0.117329  0.60753
## 24  0.03851  0.57991 -0.70662 -1.10691  0.533700 -0.10095
## 25  0.61401 -0.01017 -0.51875  0.25795 -1.076732 -0.24901
## 26  0.42275  0.07490  0.99168  0.37950 -0.249480  0.19511
## 27  0.54478 -0.12356  0.31406  0.41569  0.237094  0.09772
## 28  0.02044  0.43106 -0.71781  0.33274 -0.428303 -0.26278
## 29  1.23235  0.15293  0.10463 -0.07285  0.107338  0.07885
## 30  0.02214 -1.33353 -0.37271  0.38762 -0.062960 -0.48751
## 31 -0.71637  0.11204 -0.85950  0.24734 -0.066602 -0.17455
## 32  0.01756 -0.71899 -0.27770  0.01727  0.106473 -0.73172
## 33  0.78296 -0.75806  0.27650 -0.27767 -0.031297 -0.01895
## 34 -0.33590 -0.63554  1.07989 -0.07860 -0.526645  0.97933
## 35 -0.15761  0.49842  0.66426 -0.05091  0.331527  0.71522
## 36  0.53360  0.88375 -0.84613  0.03571 -0.630019 -0.08456
## 37  0.31300  0.02099 -0.05877 -0.57261  0.712218  0.05155
## 
## 
## Biplot scores for constraining variables
## 
##               dbRDA1   dbRDA2  dbRDA3   dbRDA4  dbRDA5   dbRDA6
## T_av         0.63982  0.25527  0.1662 -0.34674 -0.2289 -0.48193
## O2_sat_av    0.02371 -0.02938 -0.8854 -0.18557  0.2035 -0.13356
## Con_av      -0.25315 -0.27391 -0.1407 -0.76998 -0.4264  0.07657
## COD_av      -0.13235  0.15034  0.4807  0.08407  0.1430 -0.57341
## NH4._av     -0.40051  0.14159  0.7569 -0.21438 -0.2051 -0.37005
## Nt_av       -0.31714 -0.23687  0.2952 -0.33830 -0.5347 -0.40917
## pool_riffle -0.34609 -0.15029 -0.4384  0.27287 -0.5547 -0.42271
## meander     -0.33563  0.52703 -0.3800 -0.21165 -0.5422 -0.13159
anova(spe.rda)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     8   1.1664 1.2909  0.148
## Residual 28   3.1624
anova(spe.rda, by="term")
## Permutation test for dbrda under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
##             Df SumOfSqs      F Pr(>F)  
## T_av         1   0.2734 2.4210  0.049 *
## O2_sat_av    1   0.1377 1.2195  0.309  
## Con_av       1   0.1613 1.4283  0.213  
## COD_av       1   0.0676 0.5990  0.663  
## NH4._av      1   0.1709 1.5131  0.202  
## Nt_av        1   0.0501 0.4439  0.784  
## pool_riffle  1   0.0657 0.5818  0.658  
## meander      1   0.2396 2.1210  0.084 .
## Residual    28   3.1624                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
anova.cca(spe.rda, step=1000);
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     8   1.1664 1.2909  0.172
## Residual 28   3.1624
anova.cca(spe.rda, step=1000, by="term");
## Permutation test for dbrda under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
##             Df SumOfSqs      F Pr(>F)  
## T_av         1   0.2734 2.4210  0.047 *
## O2_sat_av    1   0.1377 1.2195  0.317  
## Con_av       1   0.1613 1.4283  0.227  
## COD_av       1   0.0676 0.5990  0.666  
## NH4._av      1   0.1709 1.5131  0.217  
## Nt_av        1   0.0501 0.4439  0.790  
## pool_riffle  1   0.0657 0.5818  0.695  
## meander      1   0.2396 2.1210  0.065 .
## Residual    28   3.1624                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RsquareAdj(spe.rda)$adj.r.squared;
## [1] 0.06072755
RsquareAdj(spe.rda)$r.squared
## [1] 0.2694548

8.1.2 Effect of space on component community structure

# Same for spatial predictors
spe.rda <- dbrda(spe.hel_bray ~ netcen + updist, data = env_select)
anova(spe.rda)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ netcen + updist, data = env_select)
##          Df SumOfSqs      F Pr(>F)  
## Model     2   0.5154 2.2975  0.024 *
## Residual 34   3.8135                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RsquareAdj(spe.rda)$adj.r.squared
## [1] 0.06723433
mod0 <- dbrda(spe.hel_bray ~ 1, env_select[,c(9:10)])  # Model with intercept only  #edit_PH
mod1 <- dbrda(spe.hel_bray ~ ., env_select[,c(9:10)])  # Model with all explanatory variables  #edit_PH
step.res <- ordiR2step(mod0, mod1, direction = "both",perm.max = 200)
## Step: R2.adj= 0 
## Call: spe.hel_bray ~ 1 
##  
##                 R2.adjusted
## <All variables>  0.06723433
## + updist         0.04867127
## + netcen         0.04317133
## <none>           0.00000000
## 
##          Df    AIC      F Pr(>F)  
## + updist  1 54.314 2.8418   0.03 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Step: R2.adj= 0.04867127 
## Call: spe.hel_bray ~ updist 
##  
##                 R2.adjusted
## + netcen         0.06723433
## <All variables>  0.06723433
## <none>           0.04867127
step.res$anova  # Summary table
##                   R2.adj Df    AIC      F Pr(>F)  
## + updist        0.048671  1 54.314 2.8418   0.03 *
## <All variables> 0.067234                          
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RsquareAdj(spe.rda)$adj.r.squared
## [1] 0.06723433
anova.cca(spe.rda, step=1000);
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ netcen + updist, data = env_select)
##          Df SumOfSqs      F Pr(>F)  
## Model     2   0.5154 2.2975  0.021 *
## Residual 34   3.8135                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
anova.cca(spe.rda, step=1000, by="term");
## Permutation test for dbrda under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ netcen + updist, data = env_select)
##          Df SumOfSqs      F Pr(>F)  
## netcen    1   0.3019 2.6920  0.043 *
## updist    1   0.2134 1.9029  0.120  
## Residual 34   3.8135                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RsquareAdj(spe.rda)$adj.r.squared;
## [1] 0.06723433
RsquareAdj(spe.rda)$r.squared
## [1] 0.1190546

8.1.3 Variation partitioning

#Variation partitioning
spe.varpart1 <- varpart(spe.hel_bray, env_select[,1:8], env_select[,9:10])
plot(spe.varpart1,digits=2)

spe.varpart1
## 
## Partition of squared Bray distance in dbRDA 
## 
## Call: varpart(Y = spe.hel_bray, X = env_select[, 1:8], env_select[,
## 9:10])
## 
## Explanatory tables:
## X1:  env_select[, 1:8]
## X2:  env_select[, 9:10] 
## 
## No. of explanatory tables: 2 
## Total variation (SS): 4.3288 
## No. of observations: 37 
## 
## Partition table:
##                      Df R.squared Adj.R.squared Testable
## [a+c] = X1            8   0.26945       0.06073     TRUE
## [b+c] = X2            2   0.11905       0.06723     TRUE
## [a+b+c] = X1+X2      10   0.36716       0.12376     TRUE
## Individual fractions                                    
## [a] = X1|X2           8                 0.05653     TRUE
## [b] = X2|X1           2                 0.06303     TRUE
## [c]                   0                 0.00420    FALSE
## [d] = Residuals                         0.87624    FALSE
## ---
## Use function 'dbrda' to test significance of fractions of interest
anova.cca(dbrda(spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + Condition(netcen + updist),
                data=env_select), step=1000)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander + Condition(netcen + updist), data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     8   1.0740 1.2742  0.186
## Residual 26   2.7395
anova.cca(dbrda(spe.hel_bray ~ netcen + updist+
                  Condition(T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander), data=env_select), step=1000)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = spe.hel_bray ~ netcen + updist + Condition(T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander), data = env_select)
##          Df SumOfSqs      F Pr(>F)  
## Model     2  0.42295 2.0071   0.06 .
## Residual 26  2.73945                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

8.2 Infra-communities

# Infracommunities: Bray-Curtis dissimilarities are calculated at the individual host level Hellinger-transformed parasite data and then averaged within site
# A dummy parasite species is added to avoid problems with non-infected fishes
data_infra <- na.omit(data[,c(1,22:24,26:32)])
data_infra_disp <- dispweight(data_infra[,-1])
braycurtis <- vegdist(decostand(cbind(data_infra_disp,rep(1,nrow(data_infra))), na.rm=T, method="hellinger"), method="bray", na.rm=T)
meandist_bray <- meandist(braycurtis, data_infra[,1])

# Check whether Euclidean and Bray-Curtis distances are comparable
braycurtis <- vegdist(decostand(cbind(data_infra_disp,rep(1,nrow(data_infra))), na.rm=T, method="hellinger"), method="bray", na.rm=T)
meandist_bray <- meandist(braycurtis, data_infra[,1])
euc <- vegdist(decostand(cbind(data_infra_disp,rep(1,nrow(data_infra))), na.rm=T, method="hellinger"), method="euc", na.rm=T)
meandist_euc <- meandist(euc, data_infra[,1])
plot(meandist_bray[1:37,1:37], meandist_euc[1:37,1:37])

mantel(meandist_bray[1:37,1:37], meandist_euc[1:37,1:37])
## 
## Mantel statistic based on Pearson's product-moment correlation 
## 
## Call:
## mantel(xdis = meandist_bray[1:37, 1:37], ydis = meandist_euc[1:37,      1:37]) 
## 
## Mantel statistic r: 0.9906 
##       Significance: 0.001 
## 
## Upper quantiles of permutations (null model):
##   90%   95% 97.5%   99% 
## 0.179 0.232 0.294 0.346 
## Permutation: free
## Number of permutations: 999
adonis(meandist_bray ~ avlength + avcondition + T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + netcen + 
                       updist, data=environment2)
## 'adonis' will be deprecated: use 'adonis2' instead
## $aov.tab
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs  MeanSqs F.Model      R2 Pr(>F)   
## avlength     1   0.05123 0.051226  6.1160 0.11570  0.006 **
## avcondition  1   0.00393 0.003927  0.4688 0.00887  0.627   
## T_av         1   0.00874 0.008741  1.0437 0.01974  0.390   
## O2_sat_av    1   0.02116 0.021158  2.5262 0.04779  0.105   
## Con_av       1   0.05861 0.058606  6.9971 0.13237  0.009 **
## COD_av       1   0.03543 0.035428  4.2298 0.08002  0.032 * 
## NH4._av      1   0.00275 0.002754  0.3288 0.00622  0.680   
## Nt_av        1   0.01049 0.010488  1.2521 0.02369  0.293   
## pool_riffle  1   0.00491 0.004914  0.5867 0.01110  0.568   
## meander      1   0.00959 0.009588  1.1447 0.02166  0.324   
## netcen       1   0.02319 0.023187  2.7684 0.05237  0.079 . 
## updist       1   0.01171 0.011707  1.3977 0.02644  0.284   
## Residuals   24   0.20102 0.008376         0.45403          
## Total       36   0.44274                  1.00000          
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $call
## adonis(formula = meandist_bray ~ avlength + avcondition + T_av + 
##     O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + 
##     meander + netcen + updist, data = environment2)
## 
## $coefficients
## NULL
## 
## $coef.sites
##                       [,1]          [,2]          [,3]          [,4]
## (Intercept)   5.438577e-01 -7.521287e-02  4.864790e-01  2.572596e-01
## avlength     -6.884388e-03 -1.280466e-03 -5.827549e-03 -1.940029e-03
## avcondition  -9.453108e-02  4.976498e-02 -1.367366e-01 -1.391442e-01
## T_av          2.507095e-03  3.945903e-03  2.216001e-03  1.001131e-02
## O2_sat_av     1.097888e-03  1.797618e-03 -5.251344e-04 -9.855585e-04
## Con_av        1.252067e-04  1.767804e-04  2.866100e-04  6.899238e-05
## COD_av        2.766346e-03  5.270287e-03  4.180377e-03  3.645643e-03
## NH4._av      -3.209605e-03 -1.389345e-02 -2.435426e-02 -4.858725e-02
## Nt_av        -2.834506e-03  2.998526e-03  2.117586e-03  1.084555e-02
## pool_riffle1 -1.054452e-02 -1.173617e-02 -2.662374e-02 -5.705720e-03
## meander1      5.668373e-03  8.189203e-03  1.673440e-02  5.970137e-03
## netcen       -2.142602e-06 -2.167154e-07 -2.066516e-06  2.110136e-07
## updist       -1.536592e-06 -1.364493e-06 -1.425078e-06 -1.036735e-06
##                       [,5]          [,6]          [,7]          [,8]
## (Intercept)   1.859992e-01  9.431975e-02  5.239507e-01  7.121103e-01
## avlength     -9.061148e-04  9.115535e-04 -3.388699e-03 -4.874516e-03
## avcondition  -2.246177e-02  1.242866e-02 -1.607023e-01 -2.930291e-01
## T_av          9.855242e-03 -7.934316e-04  8.314717e-03  1.226973e-02
## O2_sat_av    -8.737335e-04 -5.764731e-04 -6.922634e-04 -1.430875e-03
## Con_av        7.929827e-05  1.627319e-04  1.178433e-04 -8.169731e-06
## COD_av        2.620073e-03  2.450642e-03  2.425527e-03  1.291031e-03
## NH4._av      -2.383806e-02 -1.545591e-02 -2.488679e-02 -1.121646e-02
## Nt_av         6.508375e-03  4.792203e-03  3.250168e-03  1.733526e-03
## pool_riffle1 -2.181549e-02 -1.025280e-02 -2.009409e-02 -2.039528e-02
## meander1      1.696135e-02  5.007047e-03 -1.235392e-04  5.064015e-03
## netcen       -6.091881e-07  1.199733e-06 -2.636603e-06 -2.423047e-07
## updist       -8.547704e-07 -1.413130e-06 -1.292494e-06 -6.716768e-07
##                       [,9]         [,10]         [,11]         [,12]
## (Intercept)   4.024582e-01  1.430932e-01  7.114198e-01  5.253185e-01
## avlength     -1.263684e-03  6.480256e-03 -6.097911e-03 -1.568750e-03
## avcondition   6.327768e-02  2.153909e-01 -1.325121e-01 -2.083399e-01
## T_av          2.158539e-03  7.436242e-03  6.761999e-04  2.230340e-02
## O2_sat_av    -1.641426e-04 -9.153827e-05 -1.008227e-03 -2.435431e-03
## Con_av       -8.718723e-06 -2.085945e-04  1.217167e-04  1.006248e-04
## COD_av       -3.012411e-04 -3.782117e-03  2.998923e-03  1.207333e-04
## NH4._av      -1.764703e-02  7.858097e-04 -1.745848e-02 -2.775773e-02
## Nt_av         7.561367e-04 -9.554883e-03 -6.117636e-05 -1.001816e-03
## pool_riffle1 -6.407395e-03  1.052973e-02 -2.562772e-02 -2.466499e-02
## meander1     -9.101494e-03 -6.934907e-03 -6.056336e-03 -5.635160e-03
## netcen       -6.643610e-07  7.643835e-07 -2.271691e-06 -2.617159e-06
## updist       -1.278343e-06  1.330479e-07 -7.875475e-07  9.160172e-07
##                      [,13]         [,14]         [,15]         [,16]
## (Intercept)   3.672792e-01  6.122057e-01  2.184547e-02  3.964502e-01
## avlength     -2.868565e-03 -7.576375e-03  1.666613e-03 -4.641591e-04
## avcondition  -1.957521e-01  7.839817e-02 -1.507661e-01 -2.834975e-01
## T_av          6.543640e-03 -3.778705e-03  1.269910e-02 -6.279850e-03
## O2_sat_av    -1.983972e-04  1.375183e-04 -1.235877e-04  8.722842e-04
## Con_av        2.378346e-04  2.064674e-04  1.856637e-04  2.705789e-04
## COD_av        3.321870e-03  1.401488e-03  3.425972e-03  3.598149e-03
## NH4._av      -1.721518e-02 -1.323472e-02 -2.514115e-02 -1.960661e-02
## Nt_av         3.107012e-03  9.907581e-03 -2.455106e-03  2.484041e-03
## pool_riffle1 -8.535036e-03 -1.634315e-02  2.783916e-03 -1.866677e-02
## meander1      5.367622e-03  2.477360e-02  8.039477e-03  2.416684e-02
## netcen       -2.042112e-06 -3.535570e-06  1.554878e-07 -1.256661e-06
## updist       -1.439341e-06 -1.338057e-06 -9.098917e-07 -9.217761e-07
##                      [,17]         [,18]         [,19]         [,20]
## (Intercept)   2.493115e-01  8.152537e-02  3.929447e-01  3.545752e-01
## avlength     -2.521561e-03  3.450389e-03 -2.006019e-03 -4.380332e-03
## avcondition  -5.535822e-02  3.380327e-02 -7.982891e-02 -1.249622e-01
## T_av          1.577542e-02  1.829433e-03 -3.257684e-03  5.842857e-03
## O2_sat_av    -3.670857e-04  1.115173e-03  1.586402e-04 -2.732561e-04
## Con_av        9.029447e-05  1.690298e-04  3.073729e-05  2.848146e-04
## COD_av        2.382621e-03  1.725383e-03  2.016596e-03  3.868612e-03
## NH4._av      -1.804147e-02  3.178641e-03 -4.612758e-03 -2.216283e-02
## Nt_av         3.863537e-03 -2.837115e-03  2.887095e-03  3.626124e-03
## pool_riffle1 -6.032976e-03 -2.395194e-02  1.614506e-02 -2.226198e-02
## meander1      9.922600e-03  2.575902e-02 -1.634898e-02  1.245716e-02
## netcen       -2.083832e-06 -2.868632e-06  3.331980e-07 -2.097165e-06
## updist       -6.410051e-07 -1.222135e-06 -5.676478e-07 -1.325414e-06
##                      [,21]         [,22]         [,23]         [,24]
## (Intercept)   3.775391e-01  1.503970e-01  2.250218e-01  4.573949e-01
## avlength     -2.398519e-03 -2.089041e-03  1.704741e-03 -4.205541e-03
## avcondition  -1.783264e-01 -7.805221e-02 -2.415759e-01 -7.956202e-02
## T_av          8.668038e-03  9.723828e-03  1.330985e-02  3.519712e-03
## O2_sat_av    -5.721243e-04  1.421863e-04 -3.206484e-04 -1.767363e-03
## Con_av        3.611625e-04 -1.233660e-05 -8.074887e-05  7.022169e-05
## COD_av        3.063339e-03  1.594269e-03  1.418966e-03  2.592955e-03
## NH4._av      -1.613161e-02 -1.470376e-02 -1.487983e-02 -2.498722e-02
## Nt_av         1.587171e-04  7.708938e-03  1.771918e-03  7.708403e-03
## pool_riffle1 -2.435808e-02 -8.033741e-03  3.562517e-04 -2.123952e-02
## meander1      1.578138e-02  1.091345e-02 -1.620349e-02  9.757328e-03
## netcen       -3.310124e-06  1.502106e-06  1.297669e-06  7.740343e-07
## updist       -1.271056e-06 -5.708792e-07 -8.476200e-07 -1.029088e-06
##                      [,25]         [,26]         [,27]         [,28]
## (Intercept)   6.034100e-01  4.057286e-01  3.512245e-01 -6.049687e-02
## avlength     -4.026509e-03 -5.057274e-03 -3.273197e-03  1.120816e-03
## avcondition  -2.587040e-01 -4.526089e-02 -1.880925e-01  1.101614e-01
## T_av          2.666839e-03 -1.252435e-03  1.171091e-02  1.113716e-02
## O2_sat_av     4.608734e-04  1.746840e-03 -4.150943e-04 -2.836705e-04
## Con_av        2.772668e-04 -3.149822e-05  2.057587e-05  1.134627e-05
## COD_av        3.414552e-03  8.643396e-04  1.701807e-03  1.467592e-03
## NH4._av      -8.437314e-03 -9.353963e-03 -1.221150e-02 -1.507347e-02
## Nt_av        -3.042008e-03  8.250434e-03  6.560634e-03  7.856403e-03
## pool_riffle1 -1.612736e-02 -2.304926e-03 -4.697692e-03  2.871501e-03
## meander1      1.555900e-02 -6.834422e-03 -6.892891e-03  1.670464e-02
## netcen       -4.516532e-06  6.536252e-08  4.178064e-07 -1.139741e-07
## updist       -1.004042e-06 -8.459542e-07  5.086260e-07  1.580361e-07
##                      [,29]         [,30]         [,31]         [,32]
## (Intercept)   5.411230e-01  2.798404e-01  2.012307e-01  1.754865e-01
## avlength     -5.499696e-03 -1.806170e-03  6.207745e-04  3.526583e-03
## avcondition  -1.657150e-01 -2.368554e-02 -1.803869e-01  6.531869e-02
## T_av         -1.666067e-03  1.050303e-02  1.827691e-02 -4.432781e-04
## O2_sat_av    -1.458978e-04 -6.885352e-04 -1.052350e-03 -4.887270e-04
## Con_av        3.310512e-04  1.118422e-04 -3.615548e-05 -1.373777e-04
## COD_av        4.519706e-03  1.850090e-03  9.873455e-04 -3.841630e-04
## NH4._av      -1.908581e-02 -5.427594e-03 -2.546420e-02 -1.039064e-02
## Nt_av         2.459344e-03 -3.280792e-03  7.125438e-03  2.602391e-03
## pool_riffle1 -2.776719e-02 -2.061912e-03  7.563372e-03  2.522503e-02
## meander1      1.501418e-02 -8.648484e-03  1.197594e-03 -2.724023e-02
## netcen       -3.093052e-06 -1.357062e-06  6.499642e-07  3.058410e-06
## updist       -1.500177e-06 -2.615530e-07 -4.545058e-07 -1.236302e-06
##                      [,33]         [,34]         [,35]         [,36]
## (Intercept)  -9.926329e-02 -1.480425e-02  1.089886e-01  3.596503e-01
## avlength      4.335006e-03  1.033814e-03 -9.915825e-04  4.009826e-04
## avcondition   1.949696e-01 -4.728744e-02  4.591265e-02 -1.226052e-01
## T_av          1.536676e-03  1.917641e-02  1.128600e-02  5.420576e-04
## O2_sat_av     7.134183e-04  1.585385e-03 -7.126774e-04 -4.668302e-04
## Con_av       -3.752504e-05 -6.760566e-05 -5.178517e-05  1.385763e-05
## COD_av        5.479538e-05  6.218814e-04  2.718617e-03  2.249487e-03
## NH4._av       1.808783e-02 -8.012365e-03 -4.491819e-02 -1.750323e-02
## Nt_av        -5.949936e-03  5.427836e-03  1.507993e-02  1.596337e-02
## pool_riffle1 -1.132603e-02 -3.017789e-03 -5.284129e-03  1.761631e-02
## meander1     -7.888497e-03  3.928058e-03  4.956637e-03  2.447158e-02
## netcen        1.799926e-06 -1.746930e-06  5.266375e-07 -6.522442e-07
## updist        5.942911e-07  2.912431e-07  8.615626e-08  8.147668e-07
##                      [,37]
## (Intercept)   4.664490e-01
## avlength     -1.423928e-03
## avcondition  -1.186889e-01
## T_av          1.169964e-02
## O2_sat_av    -1.672003e-03
## Con_av        7.064826e-06
## COD_av        1.484116e-03
## NH4._av      -2.993290e-02
## Nt_av         6.515725e-03
## pool_riffle1 -1.512110e-02
## meander1     -2.765644e-03
## netcen       -1.796119e-06
## updist        1.206938e-07
## 
## $f.perms
##                  [,1]          [,2]         [,3]         [,4]          [,5]
##    [1,]  0.3801145663  2.7056211854  1.483657533 -0.278562971  1.1822156008
##    [2,]  0.0752748618  0.7437230511  1.354511330  0.125085560  2.5049269601
##    [3,]  0.4491885507  0.4699545258  0.428958337  0.877077976  0.4184159851
##    [4,]  0.8620149452  1.2718856976  2.085752120  4.355769511  0.5839857473
##    [5,]  2.1758722839  0.1322823381  0.274673803  4.653055913 -0.2287795144
##    [6,] -0.1654889150 -0.2060841473  2.357695685  1.403741708  0.2027964238
##    [7,]  0.4548028613 -0.2607403104  1.242845113  0.039981956  2.3596960264
##    [8,]  1.3635094472  0.5990752351  0.397499376  0.501293902  0.5256907685
##    [9,]  0.2549926245  0.2449082104  0.137121931  0.607183394  0.8927898096
##   [10,]  2.0829944456  1.2745951772  0.676069405  0.806620188  0.7947295199
##   [11,] -0.0456875167  1.8986451607  0.137795040  1.690545145  0.7986318633
##   [12,] -0.1074031340  0.7771250432  3.613326244  1.635354499  0.1026507103
##   [13,]  0.7256707470  1.1884853968  0.394766177  0.043898642  0.4963612515
##   [14,]  0.0952129435  0.5729074778  0.976376791 -0.108593034  0.9365829573
##   [15,]  0.4905414554  0.1977839941  0.951472180  1.590876172  0.1605402190
##   [16,]  1.3837754357  9.9144326984  4.670619364  0.386800655  0.3358365653
##   [17,]  1.6951418969  0.5973844190 -0.158890160  0.105350226  0.8034096858
##   [18,]  5.0285137814  0.1290078407  2.904054989  1.044073123 -0.0817006747
##   [19,]  1.3538767339  0.6236096725  0.108874503  0.306143837  0.6159352388
##   [20,]  1.4880519797  2.4972617218  1.330629026  0.380642748  0.0507743019
##   [21,]  1.2994305115  4.8791494026  1.206475760  0.757893126  0.9654562351
##   [22,]  0.0892688115  1.2400292932  0.982865993 -0.132360076  1.1821245430
##   [23,] -0.1150981502  0.1131422218  4.592522004  2.925104541 -0.1053834636
##   [24,]  0.1596578715  2.5246089396  0.815190665  1.209447668  1.8033392356
##   [25,]  0.0995777378  1.5576240166  0.499983645  0.377200257 -0.0045452946
##   [26,]  0.5377456616  0.3338557294  0.905980453  0.288422247  1.0137637937
##   [27,]  0.7903829214  2.2911887855  0.670865362 11.059108710  1.7118816014
##   [28,]  1.3582212386  1.4575562951  5.379600751  0.489148020  1.5480135521
##   [29,]  2.1713078591  0.6301170655  1.617679092  0.198466311  0.8975342546
##   [30,]  2.1773536059  0.5761896607  0.689572820  0.253966795  1.1781255208
##   [31,]  0.3206328627  0.1742335826  0.501383679  0.003977202  2.3241271628
##   [32,]  1.0737720619  0.7613663046  0.089049648  0.509817767  0.8075802543
##   [33,]  0.6713668257  1.7409605082 -0.149413880  0.684004080  5.6574548790
##   [34,]  1.3320939906  1.5155845179  0.701510545  1.578370282  0.7919368828
##   [35,]  0.8523306803  0.9165769026 -0.294324258 -0.100489820  0.6132511852
##   [36,] -0.0234451606  0.3281165208 -0.126269263  0.746419536 -0.0985869166
##   [37,]  1.7352439663  4.2040483821  1.612428813  0.332667555  0.4279498210
##   [38,]  0.4971254422  1.6483515560  2.262685812  0.340459232  0.2570874900
##   [39,]  0.2009194285  0.7121760864  2.070363004  1.543297456 -0.6656348573
##   [40,]  4.2660166079 -0.1439730469  1.747034260  0.046794955  1.0760637906
##   [41,]  0.3992465266  1.6286970827  0.058443246  1.896999329 -0.1929586325
##   [42,]  0.0945037006  4.7909242132  0.357118914  1.246863995  2.1873506946
##   [43,] -0.1001649687  1.3940896322  0.456819676  0.262287617  0.1857513273
##   [44,]  0.0272577142  0.1576587005  0.884839655  0.523524642  3.5652946397
##   [45,]  1.6198814953  0.7318668569  0.241774460  0.227240662  2.1048032161
##   [46,]  0.1914361448  0.4136031889  1.044134370  2.718716122  0.3651273869
##   [47,]  1.3415712215  0.2759874701  0.110926962  0.877368276  0.6646515345
##   [48,]  0.1678637395  0.2345765050  0.066532673  0.341940694  1.3754957411
##   [49,]  0.6013249197  0.4220318107  0.442286120  1.384243909  1.5996776343
##   [50,]  0.1107419153  0.9282420776  0.282349107  0.848939952  2.5873061829
##   [51,] -0.0735101741  0.1778475157  0.618559451  0.456637668  2.0243443092
##   [52,]  0.5920495251  1.2130717984  2.458009611  2.964860321  2.0534522199
##   [53,]  0.1059500911  3.3741699469  0.639436444  3.108614725  0.0039596368
##   [54,]  1.0161057015  0.8899572673  2.221900771  0.290521218  0.4633707661
##   [55,]  1.6943110479  0.9388993202 -0.131554624  2.428545133  0.0469814140
##   [56,]  0.4705418342  1.0441115294  0.496949197 -0.480562295  0.2270558090
##   [57,]  1.1689436354  2.7981309548  0.789905098 -0.037184859  0.5568151664
##   [58,]  0.7728944113  1.2550634115  0.090150485  3.336034511  0.1444876928
##   [59,] -0.2068201182  0.9193096936  2.547911449  1.044308145  0.6080605296
##   [60,]  0.3502060374  1.1080300909  2.685462786  0.026468423  1.1878928050
##   [61,]  0.6112310693  0.7342013959  0.989292733  0.557766685  0.2404145069
##   [62,]  1.7354101139  1.6636443795  2.380343661  2.016164676  2.3378100018
##   [63,]  0.8267768084  0.6214539841  0.099792428  0.366911445  0.4239022213
##   [64,]  0.3323393291  0.1297614077  0.415502519  0.993825319 -0.1143526757
##   [65,]  0.2123357256  0.9070146123 -0.223025496  0.271452069  0.6350820575
##   [66,]  1.0494498210  1.2073514112  1.477210055 -0.084245228  0.8988835979
##   [67,]  0.0972920883  0.1912938587  0.779626323  0.648866555  1.0334787867
##   [68,]  2.5908093868  0.1225294718  0.834924965  1.448982495  1.8684547798
##   [69,]  0.9158915169  3.1509788801  0.246374275  0.415155725 -0.4445556152
##   [70,]  2.0978365664  0.0470773593  4.906395144  0.853466065  0.4609904050
##   [71,]  1.5418861441  0.2636718823  0.378486421  2.352067721 -0.2353263831
##   [72,] -0.2680287293  0.0294666855  0.504494507  1.209782000  2.5793852883
##   [73,] -0.2669108345  0.8237385900  1.230105878  0.436584050  2.7272307236
##   [74,] -0.0877672885  2.5167988123  0.545063882  0.416384476  0.9199122783
##   [75,]  0.0700434035  1.2654259390  0.747905501  1.275614475  0.5164151705
##   [76,]  0.1383764037  0.3072234832  1.131837715  1.769835327  1.3139195119
##   [77,]  2.0027527972  0.6092853814  0.414152084  1.347312924  0.8609376819
##   [78,]  0.4219358204  7.1043634717  0.568486890  4.013701038  0.4261238208
##   [79,] -0.3414237157 -0.2840989379  1.057318656  0.872475175  1.7348315758
##   [80,]  1.0785431816 -0.1394640083  2.584038904  0.966396780  1.1762290103
##   [81,]  0.6369911364  2.4918483683  0.438417435  0.158156696  0.9256434000
##   [82,] -0.0349307926  0.7887403280  0.403313593  1.713560218 -0.3028927685
##   [83,]  1.2047800602  0.1498343790  3.329375011  0.948482449  1.7924780994
##   [84,]  1.9163033651  0.0592434636  0.883733123  1.134514838  0.3435523458
##   [85,]  1.8494830602  2.0149508371  1.868402184  4.499537957  2.8662606918
##   [86,]  3.3038198087  5.5750668283  0.012625541  0.891069027  1.7614711349
##   [87,]  0.1271839150  0.4824737976  1.989908056  0.962839284  2.2879839730
##   [88,]  0.8068113802  2.0565948672  0.095116583  0.734793232  0.9025763391
##   [89,]  0.5420979738  0.4707256193  3.480312570  1.044008236  2.6135048955
##   [90,]  0.7497677043  0.4433866251  1.790763413  3.250586547  0.2760098423
##   [91,]  0.5069864851  0.7082326253  0.703550681  1.655755387  0.5490544313
##   [92,]  0.2639524444  0.5962992076  0.783641130  0.219932246  0.6219716577
##   [93,]  0.5036674264  3.2750526695  0.362835020  0.842363440  0.7034724038
##   [94,]  1.2689469437  2.1422096044 -0.058008988  3.277367294  0.5131974501
##   [95,]  1.5487851709 -0.1621160983  0.393347265  0.041936118  1.3683628167
##   [96,]  0.0127772399  2.8022215214  0.231270951  0.150910463  0.4906551922
##   [97,]  0.1973438008 -0.3351799502  1.060599125  0.253387890  0.7160175380
##   [98,]  0.7687774034  3.2045509570  1.405305693  0.121335252  1.5092832441
##   [99,]  0.1400460053  2.0343867872  3.826038654  0.974056981  3.0207973398
##  [100,]  1.2679633526  3.1595827591 -0.229949387  1.426201422  0.3720476685
##  [101,]  0.4959997022  0.8085737875  0.500059308  0.952880014  0.0973026524
##  [102,]  0.4552367485  0.2602133873  0.787491575  0.258339003  0.3121865796
##  [103,]  1.2676073135  0.1390461858  0.609551416  0.614725913  0.2820666838
##  [104,]  0.7283076533  0.3535729635  0.732324906  0.705767636 -0.1452055056
##  [105,]  6.0357669659  0.4481877816  1.018883751 -0.010174523  0.4603586508
##  [106,]  1.4616616114  0.3180814350  1.121594041 -0.193420856  1.0178913641
##  [107,]  1.2995850765  0.6351966011  2.697339820  0.925321687  2.1532671913
##  [108,]  3.2455514485  1.5272924763  4.764098048  0.004197780  0.5008192181
##  [109,]  1.4964469502  0.2326348047  1.196863618  0.005744838  1.1480998679
##  [110,] -0.2780343723  3.6815227620  1.493955191  1.443818966  0.3852681621
##  [111,]  2.6444480034 -0.0530561351  0.284551847  0.219957427  3.8258216404
##  [112,]  0.7361542593  0.6591443598  1.224892139  0.327212909  1.9231146080
##  [113,]  1.4073105769  5.9395686773  0.670007502  0.360988701  1.9982357607
##  [114,]  1.4525652300  0.5907544563  0.846488041  0.586718611  1.3442494186
##  [115,]  0.4800912260  0.3142595252  1.307783570  1.657828028  0.3186704775
##  [116,]  0.3664441581  0.4487510289  2.849192293  0.929428199  0.2648747910
##  [117,] -0.1388058842  2.5772392283  2.689125437  0.331020519  0.2988524821
##  [118,]  0.4449407738  0.0817052325  0.417541077  2.809157392  0.1470637739
##  [119,]  0.5754670375  2.0966847153  3.689925781  0.622048927  0.3252943763
##  [120,]  0.5675139230 -0.0223559774  0.276105230  0.993853260  0.0349770227
##  [121,]  2.7172388986  1.5464386918  1.098072381  0.626726123 -0.3395358705
##  [122,] -0.0434299518  0.5518088290  2.173435089  0.507286164  2.5267002848
##  [123,]  0.9479082033  2.4922309611  1.554052998  1.117920972  0.7310892009
##  [124,]  0.6574955579  0.6152677573  0.439243924  0.728481341 -0.2132160579
##  [125,]  0.5088168586  1.0825073822  0.084132795  3.979055475  0.3650272894
##  [126,]  1.4870067279  3.1044763326 -0.039028271  1.731060758  1.4168541486
##  [127,]  2.9064837902 -0.0317451868  0.088882092  0.162634554  0.2675642977
##  [128,]  1.7132077662  0.7939397007  1.555575934 -0.353524894  0.5258190338
##  [129,]  0.1227534372  0.9328037092 -0.278670217  1.036166751  0.9845775909
##  [130,]  0.6208200848  0.1827450039  0.727066543 -0.340197583 -0.0750291651
##  [131,]  0.0950626819  0.3407671362  0.641112119  2.613777975  2.4274082719
##  [132,]  0.0568048911  1.2208760875  2.384347672  2.135601806  1.7186128369
##  [133,] -0.0981381774  0.3873969310 -0.061263693 -0.089318004  0.3933525259
##  [134,]  1.2024057638 -0.0666586819  0.521954652  0.791236676  0.0059147536
##  [135,]  0.5516132914  1.1009998306  4.001446818  0.144359285  2.6310535370
##  [136,]  0.0215459930 -0.0580888204 -0.086481039  0.045939385  0.3139324419
##  [137,] -0.1852544457  0.0426827454  1.890063087  1.153672058  1.3592609218
##  [138,]  0.8859110862  0.9064224966  0.207358507  4.537362631  0.9698643773
##  [139,]  1.7411217120  6.9120669300  0.772547297  2.470897207  1.9727865855
##  [140,]  3.1812462167  1.0313323823  0.678070853  0.429572029  0.9521711787
##  [141,] -0.1055626221  0.9192237429  0.909234759  2.282435198  2.0331090336
##  [142,]  0.5477298376 -0.2121843557 -0.351157992  1.791596381 -0.1145905000
##  [143,]  1.4062114359  3.1485060400  0.423524810  0.463237026  1.1599199017
##  [144,]  1.0536289401  0.3262788518  1.045349025  1.525888604  1.1985885812
##  [145,] -0.1243523988  0.1455867807  1.701526534 -0.186641959  0.6415610081
##  [146,]  1.6694813215  0.4235411134 -0.060805381  0.304122197  2.3668447976
##  [147,]  0.1945525492  1.6641080534  2.369376660  0.188979764  0.9059589835
##  [148,]  0.2181666431  0.2510427768  1.390198892  0.249937398  1.5982149718
##  [149,]  1.5189043432 -0.0061835268 -0.073035442  0.988764151  1.1784330854
##  [150,]  0.3097562740  1.1456515187  1.042685557  1.688971581  1.9153097498
##  [151,]  0.5646890918  0.4612150223  0.174502321  0.221150816  0.4994224682
##  [152,]  2.8099709198  3.1249923022  1.279679723  0.009460219  7.8956814034
##  [153,]  0.0210201114  0.2849949801  0.388428794  1.063207107  2.6671569841
##  [154,]  0.7027983608  4.1875247846  0.116351088  2.100950438  1.6705396082
##  [155,]  0.3900746360 -0.1585742167 -0.139783226  0.241462576  2.8869035092
##  [156,]  1.1614340087  1.9457046024  1.035744444  0.354815538  2.2281490192
##  [157,]  1.4762402228  2.3028869227  0.068611324  0.936749511  1.2939564362
##  [158,]  2.0993075668  0.5129613804  2.719474869  1.871828114  0.1244836232
##  [159,]  0.6245486155  4.0668502835  0.938852093  0.445075041 -0.2702521005
##  [160,]  1.1152246151  0.2224479575  0.515262369  1.621529953  0.4004750999
##  [161,]  0.8913757941 -0.0855345773  0.077244201  2.592633673  0.6166538001
##  [162,]  0.5660648429  0.4881327650  0.802986486  0.397966502  1.0200764766
##  [163,]  1.2323283118  1.8211137169  1.540013555  1.337264382  0.1829530101
##  [164,]  0.0589276754  0.3316065405  0.783104251  0.616204787  4.2831418880
##  [165,]  1.7212385275  1.9720063789  0.192448079  0.042949962  1.6904408808
##  [166,]  0.2154147967  1.2762713062  0.127793271  0.737667623  0.3627128664
##  [167,] -0.1882885036  1.0242346563  0.474802597  3.437044817  0.9939932457
##  [168,]  1.8690103084  0.8114302746  1.618458253  2.142869668  1.3006826524
##  [169,]  1.3673849849  0.8369875590  2.325337727  1.333515068 -0.1793602615
##  [170,]  1.3826180167  2.7139122726  0.792812203  0.114692281  5.7174105399
##  [171,] -0.1003364832  2.6517924594  0.362367063  0.128305299  1.9779639179
##  [172,]  1.5770163489  0.6087055292  0.026383521  1.034733277  0.7222958957
##  [173,]  1.0430642132  2.7201185750  3.050090669 -0.169212877  1.1124050112
##  [174,]  2.2865594750  0.3872697987  5.514847273  1.191890086 -0.1101078796
##  [175,]  0.9097156380  0.6286471236  0.078160838  0.419782793  0.2268422444
##  [176,]  0.7091738134  0.3130935484  0.446270641  0.075760381  1.8803193164
##  [177,]  0.2355276119  1.1490468930  0.463493178 -0.145953040  1.4485659771
##  [178,]  0.3423003900  1.8697627695  0.196807018  0.388837179  0.6108704762
##  [179,]  2.1065424297  0.6123327538  0.796247089  0.843447618  1.0344369860
##  [180,]  1.8095818738 -0.1934469386  1.465373679  0.067997213 -0.2221392936
##  [181,] -0.2761127347  1.4356943365  0.097523849  0.727229327  0.1039996683
##  [182,]  1.6036349861  0.4047373695 -0.026554981  0.096096263  0.5181798632
##  [183,]  1.0558658457  0.6551054017  1.006506149  0.617977408  2.0339331893
##  [184,]  0.6918509265 -0.1201556270  0.285250443 -0.226561569  0.4258553612
##  [185,]  0.4758716529  3.0323900984  1.077001969  2.773902326  1.9051062761
##  [186,]  0.5918817377 -0.2482689625  0.610612717  0.251335443  0.3787584830
##  [187,]  0.4562350358  0.3379326572  1.284414019  0.716423367  1.3656796805
##  [188,]  0.1583013175  1.3413058340  2.925950290  0.098863422  0.2599429284
##  [189,] -0.0321727670  0.2163064761  4.157150476  0.199952200  0.6808354332
##  [190,]  0.7891416772  1.7539601599  0.849400663  0.973746252  0.5910351703
##  [191,]  3.5967207860  1.7490853362  2.150195283  3.153879256 -0.1824091597
##  [192,]  0.7416711118  0.0436663839  0.888892718 -0.300831058  0.4436778692
##  [193,]  0.1389016065  1.9143219384  0.615525020  1.128847752 -0.0879189477
##  [194,]  0.1271680189  2.1865351608  0.973733320  2.801613522  0.5636676827
##  [195,]  0.3114741206  0.3509705749  0.677502568  0.881177482 -0.2875752995
##  [196,]  0.5793447143  0.8670097270  0.401909360  2.417962321  1.8809653376
##  [197,]  0.4586732525  2.6265059498  1.403837789  0.995408144  1.9984570138
##  [198,]  0.1958603917  0.2359399493  1.096198365  0.316934990  2.0364059796
##  [199,] -0.0223098888  3.8465120104  0.544305097  1.780838800  0.0886091342
##  [200,]  2.4173032204  2.7897453348  1.698314507  0.646743956  0.6315856371
##  [201,]  0.6263184387  2.3536561566  1.444070514  1.234182054  4.1372495780
##  [202,]  0.5936738393  2.8355354393  1.408615519  0.937461502  0.1276865379
##  [203,]  1.0602125531  0.6532280848  0.189431855  0.060749765  1.7736522097
##  [204,]  1.8257538648  2.9953592950  1.549487904  1.691625237  0.0474338440
##  [205,]  0.2356219825  0.0530972252 -0.262916800  5.350541965  0.7213599091
##  [206,]  3.5857099402  5.1747437539  2.084692105  0.779503147  1.6399621707
##  [207,] -0.1069824547 -0.2076886161  0.746894996  0.394100438  0.1912654295
##  [208,]  1.1307013587  1.2309700743  0.158492120  1.463470891  8.5655431205
##  [209,]  0.2988213441  0.8919695004  0.065149639  0.076772690  1.2565592823
##  [210,]  0.7368468264  1.5855957718  1.763520153  0.037788566  0.8824346441
##  [211,]  0.6565210365  0.8276195051  0.769681866  0.089475649  3.5971456381
##  [212,]  0.1101170660 -0.1572948041  0.008050773  0.904423652  0.5103515939
##  [213,]  1.3484020333  0.7562237429  1.396527349  0.869106722 -0.1584850450
##  [214,]  2.1516287319  1.3632993489  0.853613983  0.090330281  0.4932102586
##  [215,]  0.3024817569  1.7316875089  0.740650318 -0.013315134 -0.0098709226
##  [216,]  2.1928226259  0.6018539570 -0.100152452  0.835069768 -0.0629916856
##  [217,]  1.3716534476  0.7484269567  1.463747708  1.883739254  2.2728907363
##  [218,] -0.2346531607  0.8801510587  0.369264720  1.339568524  0.0677888295
##  [219,]  0.8338921609 -0.0854050039  0.500049310  2.550789519  1.2946483950
##  [220,]  0.0779641175  0.2602497438  0.097246844 -0.293915215  0.1035404603
##  [221,]  2.5876784431  1.2515885572  0.112959352  0.208366102  0.9916461221
##  [222,]  3.0325478650  0.8334383133  0.079879815  3.181457947  0.5109540269
##  [223,]  1.4164411456  0.2914990104  0.672935005  1.667945595  1.2812670277
##  [224,] -0.1866439523  0.2605609955  0.101864263  0.344999934  0.8464159330
##  [225,]  0.6977156250  1.4226961606 -0.135113381  1.234552605 -0.2014274850
##  [226,]  1.7374023150  2.8254033239  0.139953801  0.133558872  0.2850736342
##  [227,]  0.3636330593  0.9012179626  1.527051512  0.501172136  1.2203595349
##  [228,]  0.9247841973  2.6325462509  0.854433960 -0.152777763  2.8973767009
##  [229,]  3.4816536896  0.1257361984 -0.249476375  0.374196408  1.9665951791
##  [230,] -0.0346875026 -0.0763609318  0.101971776  0.016354324  0.8294714295
##  [231,]  0.9510205372  0.5491315899  0.810067868  0.101420312  1.5023008015
##  [232,]  0.7614626464  3.7070467145  4.367670430  1.894476607  0.7154533711
##  [233,]  0.8302845611  1.0621920877  1.452068058  1.507358290  0.0495024645
##  [234,]  0.4467507125  0.1209582103  1.476565877  0.983221205  2.2218120706
##  [235,]  0.2455325520  0.5101553764 -0.181386694  1.882135125  0.2057465709
##  [236,]  0.4215447535  0.8459474853  0.645085233  2.844136633 -0.0051884583
##  [237,] -0.3021227954  1.5466584102  1.275012549  1.220199582  1.4948979975
##  [238,] -0.1859469186  2.2996219730  0.312120811  2.043744136  1.2787203401
##  [239,]  2.1667611309  1.0147698691  0.498475374  4.095708711  2.8698331141
##  [240,]  0.6743432291  2.2517212394  0.220457200  1.172245309  0.8626031203
##  [241,] -0.1889453107  0.7848055020  1.201831750  0.338912150  0.3252203292
##  [242,]  0.6627333604  0.4247927345  0.349630289  1.217365164  0.1022276007
##  [243,]  0.8011671729  0.2241734228 -0.100606727  0.197774608  0.4493245995
##  [244,]  1.0317635521  0.1063409565  0.130135011  2.322448418  0.4477293046
##  [245,]  1.1502627068  0.5219975814  1.279664692 -0.040964579  1.4294407898
##  [246,]  0.3390227004  2.3468401707  2.317304941  0.326898623  0.5469625436
##  [247,]  0.1783039457  0.2113190161  1.588855712  0.592770819  1.4369710385
##  [248,]  1.2094118206  1.8821275806  2.096086439  1.423033806  0.2484407022
##  [249,]  0.8228410375  0.7138518720  1.303515575  1.398769573  0.4265789663
##  [250,]  0.7462041547  0.0453859361  1.578204985  0.109859368  0.3562556388
##  [251,]  0.1599322057  0.6278157179  2.468046909  0.736140388  3.9337598620
##  [252,]  0.4762413092  0.2492996017  3.486225629  1.559770438  2.4119810005
##  [253,]  1.8119114435  0.9537395759  1.077573396  0.592732912  0.3571947587
##  [254,]  3.0731751077  1.0092219470  1.866152302  0.111390782  3.3112473386
##  [255,] -0.3868186399  0.7252658698  1.620968421  0.444408038  0.2451513957
##  [256,]  2.9442606200 -0.1349202505  0.804350813  0.076923970  3.2983679902
##  [257,]  0.6093233176 -0.0378311944  0.035324187  0.938104185  1.2133151006
##  [258,]  0.6162299203 -0.1479071851  0.607085960  2.839412934  1.5772571333
##  [259,]  0.1725214033  0.8868793488  0.281129443  0.586224150  1.1278990353
##  [260,]  1.5122030363 -0.0223464016  0.091808564  1.262856843 -0.0337266842
##  [261,]  0.8783568216  1.5894645799  4.386936740  0.707624299  0.2555533166
##  [262,]  1.1673613860  0.1459404503  1.189644919  2.667708443  0.5268051269
##  [263,]  0.1320173581  0.0963354031  0.620706166  5.533752248  0.9639150729
##  [264,]  3.4875605958  0.7392152397 -0.132210027  1.490985379  0.4045960316
##  [265,] -0.0338620274  2.0141707539  0.243296789  0.073386812  0.1579652068
##  [266,]  0.1955639306  0.3887457385  0.744710873 -0.149980408  1.4680035568
##  [267,] -0.1883789953  1.4855246622  1.033338353  1.023220005  2.5400180248
##  [268,]  0.1115131208  0.4221043880  0.094479415  1.633419670  0.3168408841
##  [269,]  0.9005804091  0.9647629197  0.836897130  0.690917078  3.0609951682
##  [270,]  0.7180720905  0.1084252505  2.270062408  2.519780108  0.9016016522
##  [271,]  4.5572905586  0.0246867101  0.724873182  0.262054140  0.2173323060
##  [272,]  3.0872974141  0.4557000810  3.649314922  0.149392942  1.9806114026
##  [273,]  4.5546809201 -0.1559237367  2.731135978  0.109724895  2.7955846045
##  [274,]  1.9993777832 -0.1442936683  0.774820027  1.699632354  2.9111432765
##  [275,]  2.7688993391  0.4642450633  0.148188847  0.565173095  1.7421242328
##  [276,]  0.7338066577  0.5469334424  0.469405289  0.582331762  0.2982346125
##  [277,]  2.0595807066  1.1804036111  0.631908945  0.523740918  0.0670753521
##  [278,] -0.0301763560  1.1557211052  0.893064386  0.467782949  0.8728756512
##  [279,]  1.1784888319  0.0973521749 -0.073941689  0.595540233  1.4181862564
##  [280,]  0.0585939083  1.8847616371  1.647440349  0.782290817 -0.1524479448
##  [281,]  2.5803104223  0.7149238839  1.050977001  1.573556376  6.3174201902
##  [282,]  0.0961605498  2.0303225335  0.441996115  0.021701998 -0.0358193429
##  [283,] -0.0382706169  0.5691721602  2.013252740  2.041451618  0.8991136351
##  [284,]  0.3910291322  0.3746931598  0.472661051  0.837461255  0.3968131642
##  [285,] -0.0228733405  1.0123791832  0.667365612  0.429402353  0.9863718280
##  [286,] -0.1430991759  3.6512444100  2.391270445  6.395567136  0.5210170224
##  [287,]  4.1750007759  0.9388963369  0.688691080  0.746475930  0.2350890384
##  [288,]  4.3260172103  2.6783329070 -0.218947387  3.678095692  3.5823143379
##  [289,]  0.2517298282  1.5989632516  5.099646778  1.160314880  3.1783663674
##  [290,]  2.2597939838 -0.0668182513  4.866098872  1.045086377 -0.2199843857
##  [291,]  1.6396692281  0.2720463025  0.244594011  1.680851096  1.3421237522
##  [292,]  1.3129603970  0.2319557379  0.837073555 -0.028879889  2.0642269207
##  [293,]  1.4182259317  2.3719355706  1.661371082 -0.895450385  0.0391153687
##  [294,]  1.4360775539  0.0315165251  0.273601889  1.723291599  0.6829749234
##  [295,]  1.3038918557  0.0326058685  0.509216624  0.173640911  1.2236291887
##  [296,]  0.0048017159  1.0825161775  1.316706172  0.092662005  0.4997023425
##  [297,]  0.3005523926  1.2998876450  1.228539076  0.463253163  4.3604132273
##  [298,]  1.2674051662  0.8775312243  0.220258744  0.125498210  1.4003936654
##  [299,]  0.0029111198  0.3298503878  0.231990226  0.121600932  0.3594415862
##  [300,]  3.6171694676  0.2455666928  0.053905195  1.241265535  1.2315288733
##  [301,]  0.4384821936  0.2639152834  0.744967302  3.230185264  0.3867797587
##  [302,]  0.8427469514  0.1117142963  1.996532684  1.015736560  0.1153890433
##  [303,]  0.1665754794  0.1604065039  2.779915256  0.071457311  0.3747251731
##  [304,]  1.2676086657  3.8217830202  0.018340428  0.646531365  0.8862405751
##  [305,]  1.5948996105  0.5569514660  2.712528187  2.867948388 -0.0070311179
##  [306,] -0.1904223090  0.3428678438  0.022274385  0.788207695  0.0289800042
##  [307,]  1.0639878551  1.2763769484  1.700611199 -0.041539151  1.2746037386
##  [308,]  0.5532705075  0.6865405066  0.274994905  0.068653570  0.9478153243
##  [309,]  0.1435998225  0.5986222398  0.496494163  1.605115008  2.4802725814
##  [310,]  0.4381155061  2.7353831421  1.687534703  2.141403545  0.2322599965
##  [311,]  1.6611921488  2.3588350094  0.015884222  1.217230342 -0.0415802027
##  [312,]  1.0409566432  0.4766537116  0.176438137 -0.078036738  2.8127184855
##  [313,]  1.9699288367  3.5514070972  2.258481462 -0.156897294  0.4670840829
##  [314,] -0.0334116120  0.1693321900  0.069734465  0.543078794  0.6979544435
##  [315,] -0.0727264547  0.1961535372 -0.286695289  0.934958872  1.2148120966
##  [316,]  1.5902420351  0.1223583727  1.877236919  4.898308016  0.5051693917
##  [317,]  0.8873413036  0.0656623867  0.526288789 -0.104022334  2.7982211195
##  [318,]  1.9969655746  0.3688986446  3.312743211  0.924032226  1.0442591665
##  [319,]  0.9232563315  0.8159798458  1.807413122  0.103754640  1.5927664136
##  [320,]  0.8303913432  1.2420081132  0.920841865  2.426197583  0.4316050171
##  [321,]  0.6859295272  0.4301412523  0.498372590  1.986446744  0.5051280545
##  [322,]  0.1222596453  1.0450719417  0.120579698  2.113800815  0.3056223475
##  [323,]  0.7615309181 -0.0119882182  3.238521268  0.491231264  1.2762357061
##  [324,]  0.0767457039  0.4931112690 -0.005896226  0.482148764  2.3737057641
##  [325,]  0.9785704075  1.8045412050  4.234016540  3.683248147  7.5297734068
##  [326,] -0.2205782536  0.5708902057  1.128519374 -0.099538196  1.4920798800
##  [327,]  1.7905243473  3.6267626941 -0.026318904  1.194720846  0.6448342691
##  [328,]  3.5756015744  2.2122242608  1.702851682  1.227907233  0.5574684104
##  [329,]  4.8382924355  0.6624575342  1.728261524  0.339325944  1.4143541796
##  [330,] -0.1914533143  1.2408963988  3.565869719  0.804161981  0.2989572883
##  [331,]  0.5427865444  2.7231104451  0.821324387  0.666026157  0.2708160644
##  [332,]  0.3652888584  0.3891085430  2.807821797  0.861058667  8.7312493463
##  [333,]  2.2496244931  2.2428521366  4.366691274  5.549260151  1.8420118859
##  [334,]  0.2729424470  2.8521189618  0.462668377  0.996644476  0.1322132232
##  [335,]  0.2094621398  1.4071728597  1.534850671 -0.017903920  0.2823721907
##  [336,]  5.0482802734  0.5922645971  1.417625079 -0.179686774  2.2083857694
##  [337,]  1.2123158837  2.4914134114  0.048006080  1.691575966  0.4947548486
##  [338,]  0.1596379725  4.5731558205  0.132158965  2.577574725  2.0562124211
##  [339,]  1.3085270199  1.4315520221  0.529769565  0.230314498 -0.1348337558
##  [340,]  2.4980900735  1.0378540278  0.193291542  1.510314024  0.4929054588
##  [341,]  1.6669151054  1.2134626761  4.887500911  0.176724215  0.6408174128
##  [342,]  4.1830563065 -0.1920054938  0.411139735  0.062747362  6.1358489952
##  [343,]  0.4638474363  2.6195371428 -0.073697700  0.659939730  1.3794487153
##  [344,]  0.4557196753  0.1515212029  1.158420468  1.365324679  0.2673456377
##  [345,]  1.0302205607 -0.2498129985  3.560479558  1.736673476  2.0690224961
##  [346,]  2.6409297143  1.4548658986  0.317607570  1.620496078  2.3564150812
##  [347,]  1.3916250576  1.3229982686  1.251734921  1.109539517  2.0549000228
##  [348,]  0.7862703793  0.5072627348  1.416723977  2.202117304  0.8828783817
##  [349,]  0.8457431622  0.2801374025  0.591584780  2.182318033 -0.1580437771
##  [350,]  0.7239506923  0.5829986788  0.237579086  0.990121113  2.5249310217
##  [351,]  0.5385646626  0.1152825893  0.956552124  0.930456366 -0.0868958011
##  [352,]  0.3316455163  2.2287189938 -0.069702789  0.519714507  0.3244914638
##  [353,]  0.7237323617  1.1471189348  0.262322521  0.343608625  0.7915250151
##  [354,]  0.0844853346  2.9226594158  1.195822882  0.203183469  0.4636918512
##  [355,]  1.9489302509  1.5813741718  0.740078013  1.144084635  3.0134486062
##  [356,]  0.0352044730  0.8055591232  0.453078397  0.020170272  0.3306398946
##  [357,]  1.4164388806 -0.1290659153 -0.045875650  0.177485367  2.4326695903
##  [358,]  0.5262843582  0.4391612288  0.125046892  0.259717034  1.6905582484
##  [359,]  0.3669334888  0.5810230486  0.130416011  0.711505068  1.7879915187
##  [360,]  0.6848865109  5.9623858851  0.304527357  0.360147783  0.9446799694
##  [361,]  0.2669518432  0.2973953144  0.830982702  1.989577873  4.2866414633
##  [362,]  0.9033259550  0.0950760817  1.075121213  0.119753976  1.2586954021
##  [363,]  1.9326163216  0.9137997885  4.113924436  5.288104457  3.1345863273
##  [364,]  0.8616990032  2.7112836362  1.163566123  0.523800393 -0.3063750941
##  [365,]  1.0465267639  0.6083040071 -0.105651726  0.248318420  0.4061134957
##  [366,]  1.0980981590  0.2745079183 -0.146776981  3.311227838  0.7624570164
##  [367,]  0.0859843435  0.8198657807  1.751525126 -0.001773568  0.1347363881
##  [368,]  1.2250900346  1.5464102114  0.588636617  0.540015191  0.1882607448
##  [369,]  0.6573746598  0.5789487559  0.455287041  0.419368175  0.4159814529
##  [370,]  2.3823278923  0.9261017727  0.702074791 -0.107422626  0.2546818221
##  [371,]  0.5844592597  0.1983904487  0.394040400  1.349858203  5.4844681857
##  [372,]  0.5152478644  0.3909436204  0.411437067  1.580237078  0.1274772512
##  [373,]  1.2525544784  0.1014225497  0.360202919  1.073708499  0.4151965422
##  [374,]  0.5638951685  0.6181710994  0.794259967  0.903634754  0.6314655240
##  [375,]  1.0916920013  1.7740137055  0.484053191  0.834934205  0.3914795223
##  [376,]  0.0964600056  0.3044725850 -0.062816823  0.245893722  0.0679988179
##  [377,]  0.9468430114  0.4411261226  1.340939272  1.715493090  1.2318947305
##  [378,]  3.3272116985  0.0463741618  1.184282399  2.154303727  0.5354919405
##  [379,] -0.2140638826  0.4221710823  0.993953789  0.950079545  3.3949703634
##  [380,]  0.6257093674  0.9174592035  2.438388576 -0.124186726  1.2557528614
##  [381,] -0.0302739655  1.6332185273  0.006590174  0.646872003  0.1406815010
##  [382,]  1.7307490290  0.5317462706  0.010260816  0.604162278  0.5711332832
##  [383,] -0.1686242984  1.2465405585  0.551573677  1.056708314  0.4965458299
##  [384,]  0.9215755265  0.9663550725 -0.200297228  2.108116989  1.2866270613
##  [385,]  1.1891522209  0.2204376116  0.584392273 -0.188256235  0.5802874309
##  [386,]  2.6240753031  1.7401278242  0.241624410  0.180795293  0.1441753275
##  [387,]  0.2781026690 -0.0260522623  0.770025447  1.055071494  0.1843846639
##  [388,]  0.3288801690  1.3979770893  0.924814185  1.183495379  1.1617942833
##  [389,]  1.6852718522  1.6326403724  0.379447867  0.071112710 -0.0611833760
##  [390,]  0.3346309456  1.1480144065 -0.148911207  2.275886867  1.3400536570
##  [391,]  0.5124926147  2.2800358981  0.451986255  0.529326978  0.4064180718
##  [392,]  0.5465313860 -0.3199984753  1.258288808  0.078754954  2.1255768918
##  [393,]  0.9283821800  0.1221392053 -0.221703594  1.302644106  0.1295681438
##  [394,] -0.0705334361  0.8244068644  1.143028521  2.524150095  1.0842221599
##  [395,]  1.0926848256  2.6203824598  1.834111394  0.066890571  0.9799122601
##  [396,]  0.4922050355  0.2168341442  1.205994746  1.358591768  0.3071281495
##  [397,]  1.6839455289  1.4475187925  0.364173890 -0.218487991  1.8000971891
##  [398,] -0.0740224376 -0.0675818399  1.842199935  0.141993317  0.0852146474
##  [399,]  0.8440361847  0.1167891357  0.589745518  0.532594208  0.1402664812
##  [400,]  0.0156012854  0.4572647724  0.724853406  0.027506337  1.5089851870
##  [401,]  0.0211163836  0.4408509022  0.511617862  0.027799980  0.6793841117
##  [402,] -0.0296415993  0.4924263187  0.113823154 -0.102069894  0.7447398124
##  [403,]  0.1393129059  0.6722671902  1.341837627  0.170896496  1.2218353969
##  [404,]  0.6656271083 -0.0893129847  0.843947938  1.501308283  1.5463213392
##  [405,]  0.1200196679  0.5011079651  1.330946370  0.174239320  0.3741450386
##  [406,] -0.1207775501 -0.1243929648  0.979229615  0.160553105  2.3704553211
##  [407,]  1.2180814420 -0.5531517499  4.070341368  1.765287824  2.3455405551
##  [408,]  0.5037726153  0.0395136063  0.026023920  2.350801008  4.2266663415
##  [409,]  0.0477687312  1.2135133178 -0.112038695  2.002859684  2.4206733235
##  [410,]  4.2566179399 -0.2214740795  1.625099144  0.451291915  0.6031305504
##  [411,]  1.1147060136  0.6671393963  1.616248348  2.205587396  0.3552220021
##  [412,]  1.2415556989  2.4914710480 -0.114396538  0.133021896  0.9413258192
##  [413,]  1.6571327391  1.2035911539  0.169207233  0.981313998  0.8107183785
##  [414,]  2.5218022780  0.5723900414 -0.047695928  0.133189748  0.9740109345
##  [415,]  0.5694625489  2.0803928727  0.319950232  2.106057199  0.3822769147
##  [416,]  0.4115068912  0.2586864382  0.101494134  1.007775539  0.4605441764
##  [417,]  1.5630501486  0.5580319107  1.976726955  0.099560935  0.2738058638
##  [418,]  3.6699603846  1.3604545280  2.397942625 -0.344079748  1.2879716927
##  [419,]  0.0013814593  0.9116908331  2.314999714  2.101588730  1.8218672596
##  [420,]  0.2381126341  0.2641588353  0.281504160  0.372011709 -0.0565744817
##  [421,]  0.6171124136  0.3172178524  2.365587188 -0.391751377  0.3037859910
##  [422,]  1.1385266060  0.1900961901  1.330963992  0.444277617  1.4552508951
##  [423,]  0.1469092903  0.5327785876  0.226455500  2.624310870  0.9208173461
##  [424,]  2.3064846358 -0.1175037893  1.327873935  0.524168392  1.2453529110
##  [425,]  0.5508286471  1.4839254147  0.494197798 -0.185992043 -0.0781434016
##  [426,]  1.6310275544  0.5232678582  0.645066257  0.517791228  0.0949425032
##  [427,]  0.0118294332  1.1072189705 -0.339320097  1.187548613  0.2062140009
##  [428,]  1.6335172786  0.4238682001  0.145751806 -0.049950643  0.7351225360
##  [429,]  0.5836105188  0.0357535699  6.534087467  1.136267633  1.2905678152
##  [430,]  1.6102010416  2.3262057315  0.286984344  0.209772143  0.7632503201
##  [431,]  0.3475726093 -0.4127754854  2.733968510  2.338434837  2.7908486715
##  [432,]  0.3679771920  0.2465001258  1.229161728  0.474512803  0.2693297930
##  [433,]  1.6467056527  0.9951318447  1.974350331  1.406560140  2.5176989381
##  [434,]  0.2314784143  0.3918720561  0.302898366  3.193863425 -0.1235027709
##  [435,]  0.6516881193 -0.0897013111  0.512650689  0.457330247  0.8158974216
##  [436,]  2.8179985100  0.3915164293  0.041497536  0.755407425 -0.0507903492
##  [437,]  0.5344340027  0.4950882467  0.641162686  0.649329979  0.3957071552
##  [438,]  5.2743825169  0.8175894166  5.049037849  0.594386675  1.8999901420
##  [439,]  1.4307787426  0.3415078955  0.491117561  0.431470853 -0.0004887178
##  [440,]  2.2201065753  0.7690874510  1.037548020  0.926479606  4.3034944925
##  [441,]  0.0216638019  0.3408050626 -0.113310675  1.719923329 -0.1278844186
##  [442,]  3.4586190505  5.5964475456  2.310260036  1.707341445  0.2994602193
##  [443,]  0.8709087560  0.3790970726  0.676994826  0.464375467  0.8459889531
##  [444,]  0.8077300952  0.8579395642  0.135551911  0.198438519  1.2895562482
##  [445,]  1.0236329039  0.0110242520  1.664379615  0.230923395  0.8988186975
##  [446,]  2.9812073539 -0.0993211967  1.459452244  0.745817939  0.8062009377
##  [447,]  3.9177411712 -0.0249800539  0.227096832  0.705219658  1.5944411891
##  [448,]  1.3461333902  1.3133693944  0.257777716  2.861536418  0.8385299231
##  [449,]  1.5283932999  0.2870008392  0.437488221  0.171770816  2.3920645256
##  [450,]  0.0570793898 -0.0153846966  0.147281688  0.258296928  0.6690821418
##  [451,]  0.4363134031  0.1594995166  2.407090574  0.423145637 -0.0598687104
##  [452,]  0.6822119719  0.1600591461  1.314324922  2.357051738  0.5346805944
##  [453,]  0.2666521303  0.3496442972  0.391692447  0.053360859  0.1187172365
##  [454,] -0.0356817400  2.9400111538  0.460148077  2.326171109  0.5687076709
##  [455,]  0.2395447877 -0.0365481627  0.558214536  0.418580637  1.4971572055
##  [456,]  2.4619405194  2.0619909249  1.099843461  1.818716663  1.7549848287
##  [457,] -0.3533432726 -0.0894210912  0.253174666  0.201392796  0.5260919413
##  [458,]  0.2381431523  1.8942546925  0.314032103  0.234641427  3.3286154948
##  [459,]  2.8572377448  0.9183812171  1.362707570  0.403045668  0.7330689449
##  [460,]  0.0561349171  0.3237730036  2.406124211  2.684922954  0.0629177214
##  [461,]  3.1369276378  1.0600493418  1.635511020  0.262779847  0.3238788196
##  [462,]  1.4060352746  0.2102910811  0.593603805  0.677656679  0.8338318410
##  [463,]  0.6311628025  0.0984965369  1.102381066  0.440853983  0.1323053472
##  [464,]  0.6872603577  0.5213767982  0.059020954  0.580151726  0.7344115506
##  [465,]  0.9073624446  0.0598229018  1.243420861  0.076436196 -0.1162684995
##  [466,]  0.9134233703  0.3042542255  1.408247226  0.244213472 -0.0954824485
##  [467,]  4.6155799660  1.2822530794  5.749615457  6.476565101  5.4703690100
##  [468,] -0.0484690677  2.0293119150  0.344138581  1.134242343  1.0390643959
##  [469,]  0.0696125324  1.3400013647  0.204403062  2.446529996  1.0937796508
##  [470,]  1.2573761228  0.1650826098  0.176626679 -0.108120108  0.3587411454
##  [471,]  1.2527930273  0.3336936125  0.595288898 -0.071644208  0.0107906700
##  [472,]  0.3776408067  0.5553834205  0.179531214  0.279652568  0.8194450487
##  [473,]  0.5389344751  0.1739544460 -0.064412986  0.421019854  0.5214938712
##  [474,]  0.7182300200  2.5724390760 -0.002641194  1.419914408  3.9567245540
##  [475,]  0.4848276023  1.0728636278  0.013033658  1.234370888  0.0612286014
##  [476,]  1.7221276511  1.2056938024  0.062273434  1.594857280  0.2184811379
##  [477,]  3.5951592156 -0.1008252520  2.383712165  0.356798357  1.8781466549
##  [478,]  1.8906391969  0.9293173922  1.485739463 -0.332550909  0.5137652096
##  [479,]  0.2342103149  0.6181574570 -0.038434237  0.197201083  0.2053472085
##  [480,]  1.4963010752  0.3225895429  1.788781559  4.821975605  0.5071610743
##  [481,]  0.8650505536  0.3758508605  2.290365354  0.127556034  1.2003619828
##  [482,] -0.1841314742  0.9934930730  0.198107291  2.012150181  0.2941851744
##  [483,]  3.1408369258  0.0802547375  0.842309446  1.017023850  1.8949672328
##  [484,]  0.5307644669  1.2964475384  0.724397978  0.384746970  0.3012661918
##  [485,]  1.7245158380  3.3641250759  3.575493730  0.505286607  0.1413903336
##  [486,]  0.1276519242  0.3867257244  0.517473756  0.122774270 -0.0683155983
##  [487,]  0.3629194556  0.6826287413  1.948991539  0.392854663 -0.1221617123
##  [488,]  1.3035116553  1.0336902350  0.728722568  1.970007750  1.9303082615
##  [489,]  1.2031793344  0.2598462988  0.796184214  0.036749546  1.7993549642
##  [490,]  1.1682730939  1.2631044549  1.169854649  4.298950857  5.5815790674
##  [491,]  3.1234675574 -0.0323870900  1.698729115  0.075419376  1.2919359508
##  [492,]  2.1242432949 -0.0769581864  1.104539730  3.488200175  0.1375794971
##  [493,]  0.8655804594  0.7617455041  1.484707671  0.112827359  3.7630327170
##  [494,]  0.9863351992  0.2223566935  3.583124687  1.809148544  1.5128678650
##  [495,]  0.1969051360  2.4230636994  0.031305754  1.002871851  1.2561099696
##  [496,]  1.0474819598  0.4459832165  1.219007002  0.477968700  7.6869039500
##  [497,]  0.9703373770  0.2755727753  0.163054214  0.777259316  2.0576628643
##  [498,]  0.2734930171  4.1172697017  3.298923329  0.102728143  0.4663754073
##  [499,]  0.5357152399 -0.0850039505  0.954347572  0.358974178  0.2855215681
##  [500,]  0.1620996117  0.6911352226  0.216398413  2.984991933 -0.1065242011
##  [501,]  0.2727881683  0.6186590783  0.175849309  0.856282395  0.5252841686
##  [502,]  1.7632209919 -0.0108431882  0.287147523  5.956561631  0.8685671701
##  [503,]  0.1424666342  1.1928408243  0.506357860  0.842740765  0.9578842584
##  [504,]  2.2216668132  0.4734384029 -0.065637285  0.340505084  1.2691089565
##  [505,]  1.7773548308  3.0232473976  2.920474934  0.811131781  3.4123159686
##  [506,] -0.2035866136 -0.0318188575  0.558429583  0.283115492  2.5524653634
##  [507,]  1.6536153184  1.5422227845  1.874050079  1.211963056 -0.0099634103
##  [508,]  2.7008839267  1.8105959607  0.828281191  0.383063200  0.9176699033
##  [509,]  6.1254589567  3.6596794805  1.108297708  1.109406218  2.1506356957
##  [510,]  1.8788571892  1.1153107614  0.818468174  0.016097255 -0.0355347309
##  [511,]  0.1703517683  1.1652458163  0.629779907 -0.146189618  2.4679525658
##  [512,]  2.1498880922  5.4543579808  2.557282986  3.278567598 10.2970473389
##  [513,] -0.1561407847  0.9758089567  0.338591862  0.036224182  0.8595892656
##  [514,]  1.0987062188 -0.0228848789  0.162009508  0.325886683  4.2657647156
##  [515,]  1.5387016984 -0.1622153857  0.218718551  1.210696401  0.4936857514
##  [516,]  0.0505618370  1.2052867904  1.044518213  1.689682518  0.0722557329
##  [517,] -0.0005184355  0.9123279415  1.116090442  0.195189225  0.4565398096
##  [518,]  1.6926744351  0.0382663531  1.322279523  4.081625190  0.7569539383
##  [519,]  0.4853695870 -0.0328509223 -0.118183011  0.331320239 -0.4074706520
##  [520,] -0.0672590806  1.3634177282  0.116975982  0.564020036  0.7198113534
##  [521,]  5.1553289479  0.7050833130  1.114577056  1.648340428  0.0419683752
##  [522,]  0.6368660438  3.1328111841  1.741870764  1.601000537  1.6836523109
##  [523,]  0.7976238931  1.1901723730  0.612079978  0.681546061  2.7820923389
##  [524,]  1.0254138574  0.1358191074 -0.186158941  0.738890382  0.1563245904
##  [525,]  1.2808532830  3.9635154745  2.384923273  1.857255758  0.2097420157
##  [526,]  0.4794492459 -0.2111378597  1.098378295  1.256514912  0.5379278121
##  [527,]  0.8218166847  0.9812117343  0.659508458  0.991149177  0.2977525710
##  [528,]  0.3387346534  5.1684223078  1.649932660  0.012723736  1.2777582468
##  [529,]  1.2962165187  1.2481707452  0.076719841  1.710539460  0.2018369963
##  [530,]  0.4208640397  3.6279730822  0.562985406  3.264668661  0.6096959162
##  [531,]  0.3975199742  1.3242431098  0.305597499  3.033296397  0.0390967878
##  [532,]  1.2955634173  1.6003795661  1.047993340  0.773871639  0.8467352032
##  [533,]  0.4872176352  3.0457989056  5.738098162  1.228492743  1.0843228141
##  [534,]  0.6760763830  0.0629308411 -0.242331464  1.267662416  1.6882198628
##  [535,]  1.4266503009  1.8614666949  0.132520521  3.248176720  5.3337906701
##  [536,]  1.0411125631 -0.0290985012  1.468167331  0.764843846  0.4355085603
##  [537,]  1.5488391070  1.7418881381 -0.074607551  0.278653835  0.2883982880
##  [538,]  1.4493144162  3.4234793691  0.074794959  2.972993081  1.2138066521
##  [539,]  0.1279055303  1.8567862180  0.214555245 -0.210471933  0.7601026887
##  [540,]  0.1698498901  0.6124744345  0.668311011  0.667487218  0.3214443997
##  [541,]  3.6479952055  0.7692955887  1.893300380  0.248699983  0.4956929296
##  [542,]  0.0911694529  3.0222089185  1.454891831  0.657601122  0.2647400412
##  [543,]  2.6689444675  0.2662885343  0.965085967  1.641146902  0.6385384341
##  [544,]  0.9830194887  1.5363087357  0.133947038  0.449277334  0.2153151404
##  [545,]  0.2440781628  0.4983840462  0.096765044  0.449245905  1.0017129515
##  [546,]  1.4650796084  3.1137876295  0.900650206  2.802827455  1.0111750797
##  [547,]  0.7335780271  0.2450006454  1.098871384  0.135220905  2.7788897262
##  [548,]  1.3805952788  0.5697872243 -0.168377371  0.638982165  0.2124243937
##  [549,] -0.0602986220  1.8688263370  2.485862155  0.909664759  3.1231774234
##  [550,]  2.8083681462  0.2020594487  1.491636797  0.305763872  0.5786546859
##  [551,]  1.0338511462  1.7449572238 -0.084894053  2.195467065 -0.1970814130
##  [552,]  0.3025185417  3.9237499640  0.987401493  1.246029012  0.3358720302
##  [553,]  1.1471320258 -0.1966531415  3.450743520  3.953933629  0.3406796608
##  [554,]  4.0326953496  1.9695216128  0.581528975  0.394582388  1.9211396656
##  [555,]  0.4825848303  0.2165179738  0.381628538  0.494586898  1.3009204515
##  [556,] -0.1272595964  0.7503250262  1.315337463 -0.009927599  0.4851448905
##  [557,]  0.6870053850  0.6160366098 -0.024898411  0.150565018  2.0469453038
##  [558,]  0.4555227011  1.9067751139  2.695365314  1.352802199  0.8045993211
##  [559,]  0.9322430427  0.1311962459 -0.128197223  1.658498014  0.0964037684
##  [560,]  0.4320064878  0.8263684487  1.121779839  0.545813720  0.5573386523
##  [561,]  4.2580595143  1.1256755309  0.180034132  2.801352040  0.2920732576
##  [562,]  0.7319087105 -0.0319331515  0.121738772  0.371009105 -0.1093262188
##  [563,]  0.7636390466  2.6624221966  0.141825962  3.393695866  0.7010702135
##  [564,]  0.0819128375  0.9533507084  0.915054316  0.479071177  0.1854333365
##  [565,] -0.0026847607  0.0476757128  1.543440517  1.142343171  0.0671608773
##  [566,]  1.0127722908  1.5193545018  0.798078654  1.865217707  3.4366702264
##  [567,]  0.8655589510  0.0591998628  1.702741357  6.196545831 -0.2132396215
##  [568,]  0.7051261307  0.7236739548  2.603651440  3.046322178 -0.2096891006
##  [569,]  1.9456308298  0.1753158149 -0.173994675  0.303922052  0.6842671976
##  [570,]  1.6259650071  4.6670553749  0.115503478  0.340341878 -0.0284363072
##  [571,]  4.7579708126  1.2936028387  0.126228024  1.876967204 -0.1095729447
##  [572,]  1.8595085995 -0.2258795628  2.231819010  0.075550057  1.9042423905
##  [573,]  0.8392922707  0.5302575208  0.916079123  0.114715975  0.4574887636
##  [574,]  1.3590575906  2.7511168319  0.864931132  0.503184869  0.0101674678
##  [575,]  0.2105033161  0.2730221189  0.030778370  0.163413163  0.8823181425
##  [576,]  0.2655330748  0.9972455347  3.647147748  0.555315186  0.1229689315
##  [577,]  1.1055902666  1.8785218275  1.620484926  0.179839293  1.0051373509
##  [578,]  0.0878372797  0.4462813231  1.813296395  0.234063893  1.7816959112
##  [579,]  2.0653733558 -0.0096610371  1.251901124  0.527628414  1.7867711039
##  [580,]  1.4055070968  1.9127129746 -0.068347393  0.131338793  0.3711550738
##  [581,]  0.6709347383  2.6173026985  0.599017356  0.752938700  2.0876013858
##  [582,]  0.0981786294  0.7942268475  1.213826693  1.194125578  0.3185238521
##  [583,]  0.0686515947 -0.0732240956  1.317556820  0.334221487  0.9782328616
##  [584,]  0.1454192196 -0.0609604066  1.943164370  0.092961191  0.1345861491
##  [585,]  1.0550099287  0.3922655124  1.947470674  0.024930848  0.6614204243
##  [586,]  2.5885811586  0.8473647525 -0.051866735  1.698373646  1.2129729018
##  [587,]  2.3728129531  2.5655496685  0.966335119  0.523289699  0.3611004242
##  [588,] -0.0546890297 -0.0794420470  0.282451027  1.922149859  0.1984774911
##  [589,]  0.0798384417  0.0801523099  0.198246222  0.171472519  0.9151672279
##  [590,]  1.6272042824  1.2651036288  1.481553974  0.794129588  0.9317672966
##  [591,]  1.3944303360  0.5576265259  1.403553142  0.090344906  2.6054750190
##  [592,]  1.1408030684  0.4925310079  1.728961045  1.749466508  1.3662969802
##  [593,]  0.4269652747  0.7960478344  1.727458539  0.930575494  0.5207948497
##  [594,]  0.0089930008  0.0385181812  3.217686113  0.674031514  2.0481450577
##  [595,]  1.2379614392  0.5561565231  0.170363064  0.461160114 -0.1157170209
##  [596,] -0.2146026529  2.1548448476  0.248569878  1.325238194  1.7561046276
##  [597,]  2.1720250361  0.5390872525  0.304849299  1.983033579  1.0729797311
##  [598,]  0.0220957205  0.1965451361  0.867269718  0.422343236 -0.1047142355
##  [599,]  2.2778336444  0.4642499058  2.127253787  2.207965147  0.7849578991
##  [600,]  1.6372022727  3.4042742011  1.097860029  1.218758124  0.2475689159
##  [601,]  0.8230581894 -0.2173229496  0.684142952  0.224573862  0.6606872295
##  [602,]  0.9554369145  2.6907602636  0.425736373  1.352732015  0.4770164386
##  [603,]  1.9036594658  1.3495465454  0.163952941  0.003680062  5.4209244740
##  [604,]  0.0117178558  2.0451008022  2.724931725  0.506740588  2.1749516585
##  [605,]  4.6115518393  0.3085430466  1.171154940  5.870876815  1.3512366038
##  [606,]  0.8455204742  1.4319700804  1.439681379 -0.026633414  0.4988284720
##  [607,]  6.3511027232  0.6861398854  2.213401466  2.722062569  1.5700132777
##  [608,]  1.3814001544  0.1015498111  1.325196358 -0.084496861  0.2102268108
##  [609,]  0.2618681264  1.0199927663  1.596214580  1.118220238  1.9498687407
##  [610,]  0.1230566708  0.6110060913  0.360368694  0.157473189  1.2275926102
##  [611,]  1.8910796914  0.3999741696  2.249451272  2.613901120  1.1266389091
##  [612,]  1.2961178981  0.2499546089  5.871257645  0.394932304  0.7813539530
##  [613,]  0.6768140094  0.1238548386  0.882992989  1.993132289  0.1823574651
##  [614,]  0.7978253163 -0.0028877378  0.836178906  0.310033836  0.3804218761
##  [615,]  0.0437916740  0.7040259152  1.519797700  1.157644086  0.1754988814
##  [616,]  0.1191292025  0.1960670437  1.302116743  0.398254944  0.3112014233
##  [617,]  0.2748314327  1.7476489879  1.417211860  0.596982053 -0.0565729693
##  [618,]  0.3192492026  1.1463327321  5.625862558  2.274093526  0.9241766243
##  [619,]  2.5366861223  0.0438215872  0.268589707  0.195556448  1.4331393386
##  [620,]  2.1251804815  0.8389312736  1.544103491  1.481038542  0.5792194688
##  [621,] -0.1096374473  0.6747195057  0.672252136  3.334578805  1.3415843655
##  [622,]  1.0198175239  0.3655467529  0.305543476  0.815573716  0.8528563640
##  [623,]  0.6587701696  1.0940660945 -0.072383500  2.103901776  0.3952863548
##  [624,]  1.5195486981  1.6404825931  3.866806184  2.742592673  1.4094608398
##  [625,]  1.9579983158  2.9089180916  0.108282358  3.214521919  0.7642414420
##  [626,]  0.6471550510  0.6680259485  0.460947213  1.338542706  0.9339703700
##  [627,]  0.2098823738  0.7192907609  0.178456889  2.874633847  0.5369635739
##  [628,]  0.1643263649  0.5358182872  0.155879709  0.795347140  0.1215605469
##  [629,]  0.6517903183  0.2105018081  0.041407983  1.993827888  0.9908287620
##  [630,]  2.0919811294  1.0101343961  0.702256766  3.015227601 -0.0292866867
##  [631,]  1.4095221484 -0.1550415059  0.684723638  0.491414443 -0.1005881978
##  [632,] -0.1105825177  0.4948398696 -0.042430512 -0.017407052  1.0753273311
##  [633,]  0.2112153464  1.2797761929  1.495415338  2.286392968  1.4076241363
##  [634,]  0.0592467304  0.3612814181  0.468464344  0.502167020  1.7200111137
##  [635,]  1.3619255390  2.1941346358  0.338790010  2.562119301  0.0385338548
##  [636,]  0.6799913132  2.1054100340  0.464986088  1.393077569  0.6313415857
##  [637,]  1.5910713811  0.1176609483  3.431886736  0.678128577  0.4763520444
##  [638,]  0.3059261010  1.0012771244  0.832531452  0.452294290  0.3958141420
##  [639,]  1.8918286518  0.8920741868  1.871996073  0.540507590  1.2900706414
##  [640,]  1.0108656380  0.0781161406  0.413303897  1.411969433  0.5962247495
##  [641,]  0.4675984134  0.8092738223  1.085894295  0.414360494  3.7153723169
##  [642,]  0.8838277068  1.6623129692  1.367465131 -0.141185915  0.0161382912
##  [643,]  0.6993632615 -0.0034935800  0.844439673  0.966099979  1.2492988285
##  [644,]  0.1167827180  2.7961923913  1.492108312  1.482290616  2.3411747259
##  [645,]  0.0086065272  0.1741769987  1.055123924  2.460820874  1.0156164776
##  [646,]  5.0752072120  2.1263989878  0.315963774  3.997606424  0.0318753476
##  [647,]  1.2610365952 -0.3541448443  5.641341707  5.170581683  0.4183982644
##  [648,]  0.8428514836  0.2859796652  0.637010778 -0.011263118  1.4229909213
##  [649,]  1.9505979102  0.3439248211  0.254083462  0.595896175  0.6029879317
##  [650,]  0.5004499576  1.1753784829  1.063368246  0.864098638  2.9356151170
##  [651,]  2.3309771561  1.5134105083  1.467496790  1.462921892  0.0812046492
##  [652,]  0.0889203596  0.9248946666  0.103764091  3.080494065  1.3430017170
##  [653,]  1.0417645190  0.7794465625  0.698822704  1.508355724  0.8825458603
##  [654,] -0.1362258233  0.3016891703  0.018589749  0.946286865  1.5938757688
##  [655,]  0.0070953552  0.6815916552  3.484109414  0.490914156  1.1404011490
##  [656,]  6.3976957406  1.2214469262  1.423338802  0.389423503  0.5809815210
##  [657,]  0.0461080619  0.4953479199  1.719094110  1.322648684  0.3858357592
##  [658,]  0.3946208351 -0.0282421208  1.020968121  0.186792007  0.8620356180
##  [659,]  3.1786120613  1.1547825687  0.103301161  0.258826512  2.0413778466
##  [660,]  0.1586540359 -0.0254306477  0.567235705  0.392566406  0.5208797846
##  [661,]  0.4733918622  0.6161196725  0.299170645  0.352953036  0.2647996965
##  [662,]  1.6563469734  0.2192038496  0.922800209  0.720335880  2.4231577860
##  [663,]  0.9686730366  0.7941797576  0.782558051  0.292108181  0.1208233387
##  [664,]  3.1984622198  0.2902749754 -0.091054605  0.321984509  0.1171550680
##  [665,]  0.3599762336  1.2878381583  0.425684484  1.810887461  2.0439903831
##  [666,]  1.6434829448  1.0838334666  1.066499230  1.305360340  0.0070191083
##  [667,]  0.0240349483  0.8134051964  0.919026703  0.011734204  0.3553292999
##  [668,]  0.0973436706  0.9582619402 -0.003921118  0.617313875  2.7173934349
##  [669,]  0.4730456439  0.3748986098  2.134349617  1.573147628  0.2126045263
##  [670,] -0.3832243911  3.2737065562  0.056234267  1.062600632  1.1181017263
##  [671,]  1.1252382513  0.9084076961 -0.160658267  0.180814760  0.5165908001
##  [672,]  0.1152104877  0.0032522412  0.204498557  0.924231962  0.8215924597
##  [673,]  0.0625463094  3.8144211089  0.732997503  0.462586189  0.2249929889
##  [674,]  0.0710041313  1.5784446178  1.926693602  0.655287857  0.5364981631
##  [675,]  0.7386853027  0.7712930624  2.201500031  0.112117955  0.1481535812
##  [676,]  1.0788041721  0.5347887358  0.420583755  0.120475326  0.2869075288
##  [677,]  0.9110473433  0.2435321970  0.095519396  1.408040729  1.9951385300
##  [678,]  0.3612217310  0.9515456054  1.378373951  0.867805129 -0.1386272672
##  [679,]  1.2348851126  0.5387286368  1.215018325  0.648367478  0.3336980784
##  [680,]  2.1189136778  0.6293952977  1.552784912 -0.163380310  1.2412051326
##  [681,]  1.3449213927 -0.2073974015  0.395314075  2.122768352 -0.3032778257
##  [682,]  0.3695825030  0.8974141200  3.287124727 -0.107970425  1.2371603728
##  [683,] -0.2689251884  2.9627470971  1.750896503  0.698540018  0.8882957445
##  [684,]  0.5258898205  0.5376883823  0.078165172  1.157208446  0.3814219992
##  [685,]  1.8883614565  0.6522008091  1.731384433  0.556738782  0.4510465254
##  [686,]  1.7506519038 -0.4209551058  2.923552834  0.197146694  5.1569333055
##  [687,]  1.8047554398  0.1284470647  0.177839612  0.322468650  0.8514090513
##  [688,]  0.2522288971  0.5418366637  3.158698174  0.998849103  0.3138037877
##  [689,]  2.0062822479  1.8776806951  0.130537664  0.765015990  0.2091384730
##  [690,]  1.0101899654  0.3259829099  0.211908906  0.961889207  0.3684283826
##  [691,]  0.1908773253  1.2923900856  0.906269410  1.450099770 -0.0401488575
##  [692,]  0.5364317662  0.0891149762  3.560954948  2.411029996  0.4683601537
##  [693,]  0.5127584581  1.5897472020  1.672961763  1.883911858  1.8272655903
##  [694,]  0.6987729590 -0.0017509246  0.447901050  0.288162339  0.0594884390
##  [695,]  0.2414446850  0.6239192208  1.418981305  1.030440601  1.8026358390
##  [696,]  0.4983851413  0.0556926231  1.164302124  0.391262845  0.5612570259
##  [697,]  2.7920802701  1.9220525970  0.237533557  0.782927835  6.2613167295
##  [698,]  0.4108974570  0.9675646663  1.950237176  0.943032042  0.9322376485
##  [699,]  0.4011115756 -0.1476653048  5.180169220  2.311164818  0.1576557861
##  [700,]  0.9548096626  0.0632434950  1.260083358  0.778322724  0.8261921669
##  [701,]  0.2612508717  1.4378524742  0.543760792  0.584202059  0.5380780818
##  [702,]  2.1903309089  1.0238641357  0.323528822  0.620373601  3.2238868712
##  [703,]  5.0614064971  6.9035993020 -0.093309243  2.234772567  2.0108087862
##  [704,]  1.4555216377  2.3118110652  0.531781596 -0.074119281  1.2528827966
##  [705,]  0.3664599470  1.7462574048  1.286890185  0.815556988  0.7659146004
##  [706,] -0.0656294894  0.9566792547  2.436786327  1.444193529  0.2137953026
##  [707,]  0.6296528619  0.1855728379 -0.351197164  0.066067794  0.1926222485
##  [708,]  0.3465854778  3.4585692855  0.366210541  1.724677721  0.5934479044
##  [709,]  0.0459553282  0.9517298249  0.220300942  2.623171192  1.2632604295
##  [710,]  0.4661458236  2.0518533341  0.237726129  1.335917532  3.5590251790
##  [711,]  1.6037448971  0.2530927586  0.293145968  1.252721218  0.7101546312
##  [712,]  1.8678338141  1.3804605667  0.582487080  0.180178291  1.1796723070
##  [713,]  0.6322128236  0.5179365682 -0.232116547  1.342875503  0.9452284093
##  [714,]  0.2822484884  2.2032274253  0.546375327  0.240423385  0.6031818495
##  [715,] -0.0590213051  2.4315965864  2.264469167  0.747979907  0.8862286321
##  [716,]  1.2957917393  1.0801698131  0.168470814  0.667468644  0.6541774062
##  [717,]  0.6662882628  1.6714356840  1.356356039  0.228828136  2.5038900877
##  [718,] -0.2826686624  4.5963282746  1.236709074 -0.290760656  1.8792903977
##  [719,]  0.1500893180  0.0367912526  0.171125518  0.211125116  1.7650074859
##  [720,]  1.3500715055  1.3861010616  0.909413365  0.981970605  3.4089491680
##  [721,]  1.1876494826  1.1836553044  0.603182300 -0.102675514  3.3855797691
##  [722,]  0.0025632955  2.0867092292  2.241244921  0.552334327  1.9197492096
##  [723,]  0.2092064444  2.4144651141  1.549228304  0.008887515  0.2180802976
##  [724,]  1.5163945341  0.1654330611 -0.202128681  0.991723003  2.5027852440
##  [725,]  1.2242616797  2.1602568128  1.411738905  1.268455998  2.7866855348
##  [726,]  0.0422081240  1.4676243491  0.278484276  1.507042763  2.2039879569
##  [727,]  0.9655652691  0.4785907557 -0.064570065  0.567322134  1.0976196987
##  [728,]  1.8022644138  3.7066067107  0.494109709  2.270078512  0.4791331123
##  [729,]  0.9505189536  0.4685628602  1.613552020  0.367850480  1.3973175636
##  [730,]  0.4296735289  0.2357834654  0.037161965  0.396981850  0.8377298149
##  [731,]  0.1298214536  0.2751916721  0.437611144 -0.224324203  0.1597014534
##  [732,]  0.8786518462  1.1240702176  1.356500445  0.914211251 -0.1334404898
##  [733,]  1.1704867880  0.9672865044  0.235310565  0.907386231  1.8754352412
##  [734,]  0.8519963489  0.8578478565  0.217974942  0.368073318  0.3607450662
##  [735,]  0.6537459002  2.2601128391  2.924174651  0.387971843 -0.1076288466
##  [736,]  1.3392399017  0.7892304458  0.023777085  1.148587363  1.0229700446
##  [737,]  4.5531860276  0.5818818967  0.111287484 10.159168620  3.3049200829
##  [738,]  0.2003959123  2.1291714612  1.004488008  0.439216119  0.7927126164
##  [739,]  2.5493609542  0.4530605770  1.625480850  0.308358903  0.0345150506
##  [740,]  0.7393404050  2.2418427531  0.023890070  0.432898162  0.7134284567
##  [741,]  0.2893660784  0.0803946069  0.317782062  2.916871455  0.6287170464
##  [742,]  0.3512585759  0.8802317994  0.750736896  1.400491954  1.1044062679
##  [743,]  0.0832474946  3.4193996862  0.738467800  0.034905874  1.0343236452
##  [744,]  1.6221987331  1.6929961404  0.143432201  0.833111024  0.5309482296
##  [745,] -0.1596158072  0.7949514039  0.196154108  0.200453945 -0.0699915984
##  [746,]  1.1703633790  0.6758585473  2.125653687  2.040605386  0.4983953098
##  [747,]  0.8803359822  0.5116899880  0.882264642  0.015003149  1.0412470913
##  [748,]  0.1006477083 -0.0521571502  2.010580378  0.956168937  0.5701298032
##  [749,]  1.1530150475  0.1881236228  1.056132617 -0.045584013  0.8571833248
##  [750,]  3.1519965380  0.5348742917  0.014034852  2.586793315 -0.2505896469
##  [751,]  2.5923087867  0.4051185851  2.222842868  3.291175792  4.1118766840
##  [752,]  1.0007131085  0.5374062082  1.420634265  4.246552744 -0.6366755259
##  [753,]  0.2190620365 -0.0626093796  0.193123946  0.123142269  0.4630997678
##  [754,]  0.9784965004  0.6619024590 -0.268483305  0.884885725 -0.0614734780
##  [755,]  0.2680456285  0.2201740329  1.086919666  0.256564672  0.2844176487
##  [756,]  0.7485303177  0.2143632082  0.834018152  3.226854408 -0.2210895294
##  [757,]  0.5343692042  1.2778364058  1.747800945  3.959860956 -0.2649945827
##  [758,]  0.2946193767  3.5496874324  2.719045641  0.367757960  0.7333225195
##  [759,]  0.9875160586  0.2506895907  0.657751688  0.001078894  0.4730445590
##  [760,]  0.1275119463  1.4136760030  2.252293745  1.716768863  1.3737917913
##  [761,]  3.4673690255  3.4299116551  0.975307381  0.801194292  0.0286992172
##  [762,]  0.1265726028  0.9434404894  1.099884530  1.924240279  2.9869215680
##  [763,]  2.2860073128  1.1384109549  0.699205256  3.275777178 -0.0342615325
##  [764,]  1.0577630739  0.9641865805  0.954004768  2.934079161  0.1406418869
##  [765,]  0.6079493967  2.0110650476  2.640004859  0.538992213  0.6830907120
##  [766,] -0.1536080985  2.3753952750  1.436359936 -0.126205876  0.0705421908
##  [767,]  1.2961377207  1.2258527264  2.729075489  0.750696008  1.4366734368
##  [768,]  1.6354461773  3.3544000236  0.529833776  2.579197598  0.2339146830
##  [769,]  0.4322087354  1.1948981413  0.235859968  0.435634614  1.4534410563
##  [770,]  1.1300237536  0.9114553239  0.880990741  2.218251626  0.2961337831
##  [771,]  2.2052863888  0.8122295470  0.547948864  1.557178368  4.5619961175
##  [772,]  1.0729978869  1.5880588666  0.397950432  1.742928334  1.5567385538
##  [773,]  0.3818759040  0.2050128414  0.918247624  1.541523297  2.1014308838
##  [774,]  3.6942740766  1.4502041666  0.196211668  0.642876631  0.4791831126
##  [775,]  0.1720668339  1.1519689646  0.504837472  0.543606531  1.1544209142
##  [776,]  2.8626304154  2.5502606213  2.711270037  1.563341721  1.5799484783
##  [777,]  1.8941508254  0.9105519857  0.633413191  0.477907683  1.4977408945
##  [778,]  0.5063916390  0.2884844844  0.786857108  5.543430463  0.8351955246
##  [779,]  1.7782405396  6.5269713545  0.385969481  1.093281467  0.8580668243
##  [780,]  0.1000247250  0.0180046351  0.303200802  0.465967030 -0.0027875563
##  [781,]  1.4145866329  0.2761372844 -0.179129339  0.487727292  2.6284652133
##  [782,]  2.2079276982  3.1732256961  2.436598175  1.083891946  0.5700669086
##  [783,]  0.8129604679  0.4705296460  1.277919161  0.903726558  8.2879643480
##  [784,]  0.0189440596  2.0324903692  1.991215408  0.330507750  4.5983435827
##  [785,]  1.1699541285  3.9685670201  2.303114270  1.093499698 -0.1141995742
##  [786,]  1.5270520404  0.1143566293  1.356084130  0.175014301  3.5554420699
##  [787,] -0.3653440114 -0.1867198300  5.403944382  1.244996523  0.6367969184
##  [788,]  1.2884279628  1.2888123395  1.366288589  0.053255582  0.0406754959
##  [789,]  0.7981332512  0.1958742292  0.268480147  1.302861858  0.7393862649
##  [790,]  1.4108110374  2.7220513078  2.241554472  0.713410309  3.4407966224
##  [791,]  2.5995084051  6.9406004680  0.183845101  3.236582602 -0.0007801916
##  [792,]  0.1902823281  0.8236831590  0.178562987  3.488677446  0.5562824043
##  [793,] -0.0907293244  3.4042264149  0.977515256  0.167238688  0.1491600242
##  [794,]  1.3555052049  0.3906325565  0.431283240  0.455886000  0.6874045402
##  [795,]  2.8248347990  1.6536829426  0.960487939  1.041631416 -0.0326447610
##  [796,]  1.5026162615  0.4011520101  1.288083988  2.164506010  0.0654170501
##  [797,] -0.2924639853 -0.0846666779  0.481516179  1.292967037  1.8911380006
##  [798,]  2.0624233972  0.6673500489  0.874895379  0.504268828  0.5526691692
##  [799,]  0.5068796208  0.5062401886  0.377800584  5.229209854  0.4230711918
##  [800,]  0.0230390922  0.5950872702  0.999926635  0.430254929  2.1322693875
##  [801,]  0.8348814019  0.4023536590 -0.301871246  1.925917674  0.9570077341
##  [802,]  1.2520346070  1.0371584640  5.130659094  0.681375806  3.3459967801
##  [803,]  3.2031836066  0.8129441450  3.483141259  0.946156501  2.8332298165
##  [804,]  0.6564527886  0.5889248006  0.069669167  0.810508688  0.5249394797
##  [805,]  2.2859109282  0.7779599057  0.161494748  0.696660366  2.6572715586
##  [806,]  0.7358308275  1.0798191529  0.060179397  2.180967662  2.4946705744
##  [807,]  2.5794423521  1.3111117215  0.278111070  1.139681942  0.9459274699
##  [808,] -0.1909957983  0.8898605758  0.202287199  2.239038509  1.3550819488
##  [809,]  1.0701351500 -0.0393936889  2.038453495  3.688130573  0.7533770075
##  [810,]  0.7996356848  0.1045223385  0.634256678  1.317063031  1.5820715651
##  [811,]  1.0360546156  1.5637637314  0.036407098  1.583170259 -0.1482190113
##  [812,] -0.1163201184 -0.0259229877 -0.072078593  4.218539143  0.1894235634
##  [813,]  2.6098670111  0.8006572584  2.398098934  0.189177163  0.7225071112
##  [814,]  1.9475058354  1.2711580545  1.193583615  1.705255674 -0.2332156725
##  [815,] -0.1488203176  0.3599112199  0.734313999  0.305696066  2.7227430480
##  [816,]  0.5529617354  2.2867818258  1.118153814  1.044495971  0.8804799437
##  [817,]  1.5666670614  0.2519250525  1.150673189 -0.001946236  1.1169148185
##  [818,]  0.5952679334  1.4182174686  2.149840184  1.494363566  0.6416965474
##  [819,]  2.7238341283  1.1807509500 -0.027602671 -0.256927721  1.0807293153
##  [820,]  0.5625671471  1.2004407370  2.408799568  1.777770370  2.5695500190
##  [821,]  1.7911214521  0.3255983917  1.355658078  3.402953360  0.1514834259
##  [822,]  0.1948077218  1.9954095879  0.776765797  0.886673123  0.3245632256
##  [823,]  0.6391653046  1.3892458306  0.227993666  0.231907782  0.3773518037
##  [824,]  0.2020682223 -0.0257191531  0.539595495  0.307523832  1.4419900827
##  [825,]  2.9053033343 -0.0070977713  1.876039400  0.378663696 -0.1517280640
##  [826,]  0.5834445519  0.5827896084  0.637335761  0.436662163  1.2066788392
##  [827,]  0.2527504171  3.8203473626  0.514143968  0.258694168  0.6444591877
##  [828,]  0.5181707795  1.1694322976  0.209440122  0.499207843  0.5301114110
##  [829,]  0.5900996639  0.3239858397  0.026033887  0.596244500  0.3592911196
##  [830,]  0.0637225227  2.5837813772  0.250758722 -0.069238360  0.8565596178
##  [831,]  0.5174948388  1.7560640770  1.100272841  2.927714441  0.7815295500
##  [832,]  1.3476671066  1.1570815868  0.238494177  0.498093227  3.1768912205
##  [833,]  1.8652445638  1.3822289263  0.106327190  1.422694194  0.7254406337
##  [834,]  0.2375757951  1.4328817727  0.886360596  1.280336373  1.5135802651
##  [835,]  1.1548122980  0.5770313991  1.316301499  2.386900506  1.8236974407
##  [836,]  0.3769891183  1.6819973422  0.785325511  2.044860230  0.7191518891
##  [837,]  2.0012277106  0.5439399375  0.412208088  0.460223257  0.9097876105
##  [838,]  0.2052923463  1.9002458457  0.623451107  3.148729138  3.3418534271
##  [839,]  0.8946980175  3.9063283762  0.186072873  1.131991706  1.8720313480
##  [840,]  2.4137270751  5.2149046794  5.426700010  2.575991971  2.5664423968
##  [841,]  0.1237343266  0.2345054560  0.729518015  0.241430002  1.0852547875
##  [842,]  0.1349092927  0.0689731539  2.247973339  0.271763343  0.2258039514
##  [843,] -0.3861846508 -0.0578246676  0.323894308  0.376808892  0.1800998703
##  [844,]  0.9355093825  1.3276814374  0.851215587  1.265110120  0.9898287175
##  [845,]  0.6225958589  1.8034080360  0.481478041 -0.284833780  0.8864946084
##  [846,]  0.2722691107  2.7067956326  0.388586164  4.534272505  0.9379696360
##  [847,]  4.3526108283  2.0979957020 -0.195000933  0.252978971 -0.1805448856
##  [848,]  3.2468584731  0.5508860134 -0.009167378  0.120163196  0.1286532712
##  [849,]  0.9097339480  0.2941258149  0.133426960  2.142276143  1.5953232826
##  [850,]  1.2789243565  0.6527119414  1.184539032  0.135723576  1.4986268232
##  [851,]  0.9481758915 -0.0095872744  0.394635350  2.735426197  1.6896982880
##  [852,]  0.2744895292  0.5103553911  0.219789590  0.577561446  1.2836615107
##  [853,]  0.3680780901  1.1789552770  1.367872960 -0.001834057  1.2559772138
##  [854,]  0.0249593517  1.1054822271  0.554610612  1.986768176  0.6642986454
##  [855,] -0.3892842028  2.9880292906  2.167212258  1.692017114  6.1555983873
##  [856,]  0.5908604072  2.7151021185  1.475862110  0.407935658  0.1443173135
##  [857,]  0.4167999861  0.4134400776  1.693392043 -0.133281102  1.5921017645
##  [858,]  0.5593000305 -0.1451432315  0.592669305  0.333378389  0.5714943913
##  [859,] -0.2069963782  0.8371859216  1.156496969  0.977328275  0.1062956685
##  [860,]  0.5894177710  0.8604786427  1.521666945  4.060780051  3.4561831934
##  [861,]  2.1990113926  0.3966330921  0.055116173  2.242398630  0.2605680700
##  [862,]  0.9016667032 -0.0006204587  2.495944076  0.469806828  0.5603374784
##  [863,] -0.0423694623  0.5648199839  0.546211585  0.125481203  0.4420178163
##  [864,]  0.7117584866  0.5164444521  0.799236899 -0.179673203  1.3577351605
##  [865,]  0.1445770392  1.1300889981  0.530607278  0.708555305  0.6454414421
##  [866,]  1.2724062611  0.6538678182  0.559012370  0.226964836  0.4717421479
##  [867,]  0.5044618460 -0.0816372977  0.727667085  0.084847319  0.8303344441
##  [868,]  0.3431782904 -0.1428361374  1.320818926  0.691181471  0.8132668566
##  [869,]  1.2678641229  2.0725472988  0.265058571  0.237177920  0.0258604173
##  [870,]  1.6503344015  3.8673300073  0.174716871  0.556462570  0.4330385820
##  [871,]  0.5776995834  0.1985185125  1.938303991  2.061670625  4.3213514637
##  [872,]  1.3810344096  0.2419142242  0.405504843  0.917833235  1.4944257045
##  [873,]  0.8882867903  0.0702308735  0.681782726  0.625223991 -0.0983326833
##  [874,]  0.0665077765  2.3078966375  1.587817794 -0.078381210  0.1347478226
##  [875,]  0.1478835324  0.1943659804  2.154873787  0.452183457  0.7481828269
##  [876,]  0.4381854720  1.7197195802  0.278013780 -0.185942709  1.4934294252
##  [877,]  0.2340192510  1.4792285853  0.633207756  1.671053786  0.1393640324
##  [878,]  1.2877311745  0.2582947012  0.523886245  1.346977077  0.1734657111
##  [879,] -0.0643966386  0.9849509126 -0.219529595  0.604526281 -0.0553821317
##  [880,]  6.4986492677 -0.0703065987  3.718525828  0.471708886  0.5026881632
##  [881,]  0.2014182600 -0.1956294248  4.250636374  4.675378319  1.4922804786
##  [882,]  0.3731709640  0.8530171456  2.790130562  0.052976604  2.3798925700
##  [883,]  1.3460816118 -0.0140180906  2.115048676  2.294456127  0.2329834694
##  [884,]  1.0123575735 -0.1072201810  0.140928639  0.310847614  0.5385466535
##  [885,]  2.1183134965  1.7891319142  5.061699715  2.762056374  0.4832557156
##  [886,]  0.7038399546  0.1750322869  0.134677713  0.926583303  0.0246873722
##  [887,]  0.0533500205  0.4927530847  1.285068321  1.503488048  1.8667396215
##  [888,]  0.2755895974 -0.2108115412  0.076331843  1.744519904  1.4118425840
##  [889,]  0.4891336488  0.5211272495  0.665617632  0.203945867  0.1081577404
##  [890,]  2.3276355302  0.5272503532  0.117871130  1.319756712  2.9241187042
##  [891,]  0.7506910667 -0.0774854632  0.470536337  0.581099588  0.6913743969
##  [892,]  0.9904297912 -0.0171020674  1.140931020  2.011199689  0.0895951210
##  [893,]  0.0345622202  1.1150944338  0.339170926  0.850448110 -0.1153085326
##  [894,]  0.0359935881  0.2889200480  3.112986079  1.508299268  0.7591502880
##  [895,]  0.6986169282 -0.2080769042  0.688853200  0.748468298  2.8496422289
##  [896,]  0.7920224377  1.4762746577 -0.011533133  0.871344882  0.0994684191
##  [897,]  0.2487711176  1.2832312420  1.722494957 -0.154996380  1.3966724206
##  [898,]  1.3937659145  1.2636593366  0.450212299  1.151389913  0.8128885629
##  [899,]  0.0656063250  0.2516932487  0.209170635 -0.008790003  0.9617806185
##  [900,]  0.3788477632  0.4373127831  0.154069267  0.433685243  0.3623718775
##  [901,]  1.1162148837  0.7388431474  0.943592808  0.879550754 -0.0229861563
##  [902,]  0.6310182010  0.2449754782  0.743546119  0.847155701  0.7844201871
##  [903,] -0.1813458866  1.8374208066  0.373410373 -0.249059277 -0.3156409326
##  [904,]  0.7352528002  0.6180599548  1.124545837  0.966622330  0.1197291111
##  [905,]  1.1138959913  0.0796172457  0.726535444  1.927392198  0.0926907102
##  [906,]  0.6813086148  0.9325334678  1.986274059  0.276193874  2.1206992039
##  [907,]  0.0040645085  1.1858523287  1.126785733  1.838783369  0.6915851179
##  [908,]  1.6787229397  0.7711245251  0.396606549  2.122230294  1.3222644045
##  [909,]  0.5203080755  0.3999669827  0.071318552  0.248339421  0.6245152153
##  [910,]  0.8328324209  1.1820433963 -0.215101219  1.155326629  0.3298523690
##  [911,]  3.6129867697  0.6742010537  0.014972888  0.748568733  3.9400884789
##  [912,]  0.0553348172  1.4668504755  1.273443214  0.771546340  0.2718694335
##  [913,]  1.5367626642  0.2190583806  3.438838112  0.794276976  0.6113879193
##  [914,]  1.6415827266  1.1143078235  1.622054698  0.538527286  2.6367907877
##  [915,]  0.5425318331 -0.0179732935 -0.097155641  0.615119118 -0.0121596918
##  [916,]  1.2786787688  0.7293892836  1.897562249  4.930526531  8.3398721864
##  [917,]  0.5506037807 -0.0999842391  2.728371572 -0.107186838  0.3876571737
##  [918,]  0.8099001071 -0.6490769951  0.617381703  1.826139646  0.7372019348
##  [919,]  0.2196721489  0.7390635607  0.194377725  0.702848228  1.8171671210
##  [920,]  0.6759174610  0.7795179148  0.364212733  0.740593921  1.1016918585
##  [921,]  0.5231618102  0.4131937248  1.838567380  0.770492350  0.3046182864
##  [922,]  1.0836245683  2.5621969376  0.449058643  0.598009425  0.5676349520
##  [923,]  0.7686051944  0.1486231808 -0.037058375  0.592449570  0.5377193426
##  [924,] -0.0308582925  1.9690441250  0.978652365 -0.037416691  1.6128271071
##  [925,]  3.9942148800  0.2107157358  0.148380607  0.793077845  1.9458822988
##  [926,]  3.1027019095  1.7600102886 -0.322512622  0.933273346  0.7111974423
##  [927,]  0.3059963865  1.3495261806  1.277843829  0.320479358  2.9269898114
##  [928,]  1.8611047407 -0.2050255628 -0.014356793 -0.031457434  0.9489700361
##  [929,]  0.0177637743 -0.1405138621  0.574355038  0.365712960  0.7392783249
##  [930,] -0.1142315827  0.2625794220  1.439609603  3.523180615  2.1949217224
##  [931,]  6.3477881647  0.4788658780  2.039496498  0.848472441  0.6786045462
##  [932,]  0.7962804407  0.4740565642  0.090811334  0.080659599 -0.0643365018
##  [933,] -0.1215665941  0.2601310614  1.188732801  0.084135552  0.5027608483
##  [934,]  1.6175169780  1.7006020975 -0.134897146  0.718355081  1.3983021256
##  [935,]  0.7228984541  0.5032167620  0.348305992  7.003632508  0.3116332116
##  [936,]  1.3663799723  1.5260202352  0.553171145  0.108100684  0.0270602498
##  [937,]  0.2860401885  1.2314254197  0.691232805 -0.151008944  2.6248561048
##  [938,]  1.1693142547  0.4624600113  2.953706117  0.957209432  0.2851808985
##  [939,]  0.8536335489 -0.2658406369 -0.160987723  0.260415363  1.9066233404
##  [940,] -0.1930199885  1.8231665768  0.792581400  1.366354177 -0.0184102512
##  [941,]  0.9608425487  8.5587464298  0.853588960  2.030279058  0.8649472381
##  [942,]  0.7167440365  0.6660827071  0.115834896  1.289342665  0.5678395500
##  [943,]  2.9508162746  1.1543661913  1.478387239  0.243845627  1.1686275972
##  [944,]  3.7115770044  1.8576424227 -0.152130970  0.324460977  0.9727013767
##  [945,]  0.4586230975  2.3496274305  1.899204765 -0.060245689  0.9734010606
##  [946,]  0.0584200833 -0.1798403829  0.196367611  0.420744288  1.7402924560
##  [947,]  1.5696946239  0.6443676133  0.509498910  0.381669775  1.7648095119
##  [948,]  0.2856898106  0.6419538623  2.880055967  2.224600120  1.6030366656
##  [949,]  1.5681204311  0.6729804561 -0.006969424 -0.010584874  0.0673519065
##  [950,]  1.5473736879  3.8344335579  0.691310470  0.456047584  1.4225746999
##  [951,]  0.3724693924  0.8797569538 -0.162087596  0.498346983  0.1392819545
##  [952,]  2.7100999687  2.0003254943  3.510005365  1.116802216  1.7013423949
##  [953,]  1.7636559191  0.0929840756  0.163300805  1.201375021  0.1425632301
##  [954,]  0.9171300212 -0.4821951829  0.549343823  0.757300371  1.5870176861
##  [955,]  3.7953174573  4.9950083758  2.799988493  0.919200975  0.0797304845
##  [956,]  0.4196065486  0.0594501921  2.485623413  0.404869265  0.4328184868
##  [957,]  0.3389352694  0.2135964600  0.415109206  1.548323108  0.9409364132
##  [958,]  0.6090206350 -0.0867589725  1.400548707 -0.159778880  2.1759421338
##  [959,]  1.3534859661  0.5858814639  1.159396274 -0.008503290  0.5750999616
##  [960,]  0.6889071333  3.1698012480  2.751938288  1.035929874 -0.1494223370
##  [961,]  1.2882499759  0.1308812110  3.500843206  1.667289221  1.3979249884
##  [962,]  0.2577474878  0.4100520488  1.417168563  0.301247699  0.5063852904
##  [963,]  1.1218294596  0.7956216278  0.541374044  1.378818316  0.6253320576
##  [964,]  1.0082500837  0.4513470533  0.161981502  1.360322190 -0.2307029059
##  [965,]  0.6048066942  0.4106273981  3.102918985  0.941497957  0.5631934039
##  [966,]  0.2154063825  0.3411579486  0.381012748  0.008159854  1.4273017267
##  [967,]  1.6182987328 -0.2565442952  1.268106221  1.596053765  1.7296327503
##  [968,]  1.2792225057  5.6166106139  2.262065205  1.429980548  6.0858256227
##  [969,]  1.6134530687  2.7060480778  0.212278788  1.484462561  0.3491779768
##  [970,]  0.3946663291 -0.0849647096 -0.121780934  1.807681948  0.8650151991
##  [971,]  0.6695552320  1.0557364503  0.332585434  1.188805842  2.2174927204
##  [972,] -0.2808270924  0.1187759620  0.288332505  1.285313912  0.9962276486
##  [973,]  0.3558108894  1.3092014433  0.885225270  1.339782418  0.0368311346
##  [974,]  0.5630732242 -0.0339007299  2.994268801  0.591215350  3.4877722770
##  [975,]  0.6639024152 -0.0573599181  0.003713450  1.400072462  0.5354054130
##  [976,]  1.0394366013  0.2276801727 -0.064772635 -0.124145239  0.7075164003
##  [977,]  0.8325664291  0.0109883360  0.107444539  5.182736776  1.1176656650
##  [978,]  4.9460663510 -0.1770568146  1.825646739  0.725824358  0.1826518718
##  [979,]  1.2296661511  0.6925387997  1.307403123  6.617068182  0.3416476673
##  [980,]  0.5867581199  0.3791149177  0.049758831  0.060192317  0.5203150571
##  [981,]  0.1210431617  2.4668159690  0.440051095  0.381700325  1.1305936832
##  [982,] -0.0424567569  0.9176610649  2.972562497  1.299812589  4.5860599194
##  [983,]  1.1199641217 -0.2916205759  0.082031819  1.687779552  1.8272838093
##  [984,]  1.1508058406 -0.0500255274  0.430196842  1.412204508  0.3947114711
##  [985,]  0.9839827948  0.2490480506  1.218517162  1.305887023  1.7420776949
##  [986,]  0.6253901402  1.0087257875  0.189298433  2.129418585  0.1275911972
##  [987,]  0.0239923014  0.5125437660  0.631106531  1.123867979  0.7910380429
##  [988,]  0.0745923484  1.0584455254  0.336691140  0.885466140  0.9001598087
##  [989,]  1.3080204193  0.3810902551  1.180359702 -0.074689803  0.7478007012
##  [990,]  1.5809851137  0.4889945952  0.479909896  0.509602044  0.7617443235
##  [991,]  1.0499080874  0.5084886443  0.864443144  1.595885082  0.1601012679
##  [992,]  1.0230909114  0.9134424806  1.937816940  0.426601324 -0.0810008677
##  [993,]  0.0432798059  2.3212032567  0.587060051  0.630175328  1.4426987850
##  [994,]  2.7112361540  1.1136669368  0.374961860 -0.155553727  0.7010075936
##  [995,]  3.0683300666  0.4969290755  0.013703828  0.908796329  0.2508477748
##  [996,]  1.8926352686  0.1415544360  0.191589326  0.118988549  1.3280206325
##  [997,]  2.1577314845  0.6503373444  1.429536585  1.325682032  1.3753461765
##  [998,]  0.3908603654  0.7745483311  1.393843990  1.676403170  6.3324467801
##  [999,]  0.0766322681  0.7935669580  1.707705943  1.397107848  2.4394959744
##                  [,6]         [,7]          [,8]          [,9]         [,10]
##    [1,]  1.3151685846  2.473879371  1.927612e+00  0.6924370643  4.7815747161
##    [2,]  0.4884188840  0.523395371  5.768997e-01  2.2885044926  0.0219193121
##    [3,]  2.1040394307  1.329002943  2.524405e+00  1.4467660092  0.9294676626
##    [4,] -0.0112105685 -0.011548184  7.068133e-01  3.3630236319  0.1226866769
##    [5,] -0.0661807474 -0.155150847  7.234826e-01  2.3278110177 -0.1275195548
##    [6,]  0.0953827763  1.892089955  8.925631e-01  0.8795468379  0.0709554277
##    [7,]  0.4496779932  0.841918835  4.712815e-01  0.4365837437  0.5432338095
##    [8,]  3.7432944852  3.127972706  2.157621e+00  0.1384945303  0.2741131240
##    [9,]  0.0503161515  0.115085382  2.670218e+00  3.7897934332  0.2197900650
##   [10,]  0.8280300919  0.540056720 -1.365295e-02  1.1885690701  0.0572364882
##   [11,]  2.0346795056  2.315546334  4.119921e+00  0.0479775283  0.5165281555
##   [12,] -0.3583860476  0.612147548 -8.979572e-03  0.8092326206  0.9823099607
##   [13,]  0.7202841067  5.384255096  3.019309e-01  0.7852423194  1.7351637677
##   [14,]  0.6004283684  0.480633127 -1.649184e-01  0.6542765013  0.5473131793
##   [15,]  0.5988112891  0.101200096  3.828075e+00 -0.2878143553  0.2116583314
##   [16,]  1.2301492469  1.620449322  3.529032e-01  1.6120101575  0.6237788852
##   [17,]  2.9418470668  0.816988300  1.160568e+00  0.9992891499  0.5302896006
##   [18,]  2.6600804237  2.085686860  1.147045e+00  0.6440365908  3.3143981523
##   [19,]  1.0697329775  1.045513394  1.652913e+00  0.2954879996  0.1690948542
##   [20,]  3.0724212282  0.613313662  4.437370e+00  1.6728999324 -0.0151055927
##   [21,]  0.2600980899  1.219774991  5.207380e-01  0.6044819040  0.9375487873
##   [22,]  0.2083023701  2.403908833  1.567479e-01  0.2032069989  0.8677078992
##   [23,]  0.7672723000  0.564313981  2.692716e-01  0.5185904448  0.5192169920
##   [24,]  0.7211721229  3.114849198  1.590760e+00  3.9377454390  0.2226997099
##   [25,]  1.1235152207 -0.044139422  1.753989e+00  0.5307068080  0.5574257041
##   [26,]  3.4613967936  0.140562267  3.894596e+00 -0.0793250296  0.2844012961
##   [27,]  2.9361908229  0.797868000  3.036669e-01 -0.0762857703  0.9018441373
##   [28,]  2.5899449311  0.508921461  5.391967e-01  0.2466475765  0.8160655958
##   [29,]  1.1884565530  0.482440421  1.024214e+00 -0.2076358543  0.6698916176
##   [30,]  0.5538141332  0.986119311 -5.281031e-02  0.8847052002  0.2174004992
##   [31,]  0.3933043791  0.988109040  4.330524e-02  0.4712213308  1.4677790415
##   [32,]  0.9731133117  0.098593374 -5.961158e-02  3.8488626971  0.6484167363
##   [33,]  0.5326203171  0.416263285 -3.369900e-01  0.1099712307  0.1157564530
##   [34,]  0.1069514408  1.001756187  1.160532e-01  1.2353048412  1.4464259418
##   [35,]  0.1171286530  2.724600365  1.938760e+00  2.4462852765  2.5022300949
##   [36,]  0.2708720500  0.268143475  2.053203e+00  1.1500762157  0.2393957692
##   [37,]  0.6274541922  0.762937124  2.259775e+00  0.1826981043  0.2594569945
##   [38,]  0.0260076594  0.843715241  1.388240e+00  3.2837490982  0.6034949661
##   [39,]  4.1003482536  0.283269591  3.339982e+00  5.8429508469  1.2673719253
##   [40,]  0.7047724130  1.178443615  1.816264e-01  0.8003639529  1.1981182229
##   [41,]  0.2088343670  0.017724882  7.401551e-01  2.2952305033  0.4594442360
##   [42,]  2.3551833090  1.676272456  1.629215e-01  0.8009308798  0.8037305749
##   [43,]  2.5050732376  0.034879130  2.135357e-01  0.0830959304  0.9157562744
##   [44,]  1.1309801393  0.130260219 -1.880286e-01 -0.0086379109  0.9090509525
##   [45,]  0.9920682601  1.399438278 -1.637668e-01  1.3521092743  1.5738517717
##   [46,]  2.0343374929  1.680299947  2.705459e+00  0.4188256760  0.1553808509
##   [47,]  0.3498161851  0.487722084  1.953102e-01  0.8752340688  0.7422392565
##   [48,]  2.6542594073  1.430734167  1.248694e-01  1.4816726376  1.4469159455
##   [49,] -0.0802845785  0.884602233  7.681333e-01  0.1799400505  0.1377179626
##   [50,]  1.1115617129  1.021616906  8.384472e-01  1.7200227508  1.5157152719
##   [51,]  0.3881021363  0.855004425  3.263933e-01  0.0778489426  2.4259861855
##   [52,]  1.7348399843  1.843424443  7.409492e-01  0.3563550511  0.0455448567
##   [53,]  0.0786757572  2.129717980  9.718148e-01  0.8901793689  1.2608421228
##   [54,]  3.6491058081  4.690831541  8.086656e-01  0.2895150333  0.3239902463
##   [55,]  0.6125488178  0.621069594  3.602210e-01  0.2762861908  1.5151348578
##   [56,]  0.1049239548  0.464823487  9.025401e-01  2.6453115085  3.1938277738
##   [57,]  0.8668306752  0.482317519  1.338494e+00  0.4877944387  4.0576099281
##   [58,]  3.2060697767  0.255317043  6.331114e-01  2.4080509391  0.4048178353
##   [59,]  2.0458101795  0.147747553  2.232393e+00  4.5251482681  0.9813450118
##   [60,]  0.0998006177 -0.294102574  1.380637e+00  1.2875103584  0.3361107970
##   [61,]  1.9483978720  7.285787099  2.167941e+00  0.2831952252  1.6636569237
##   [62,]  1.3474080466  5.001036704  2.881811e-01  1.9645485732  1.2756632235
##   [63,]  0.4344337008 -0.287450536  7.828067e-01  3.4390986189 -0.1016786682
##   [64,]  0.1696833536  1.004506543 -1.499113e-01  1.8611639269  1.5912297844
##   [65,]  0.0689002796  0.237578470  5.194236e-01  1.1701866538  0.1299701214
##   [66,]  0.6014963585  0.030229989  1.054099e+00  0.3999694294  1.2060035780
##   [67,] -0.0505530332  0.821573794  7.108699e-01  0.1619489046  1.5281285119
##   [68,] -0.3476502619  0.062639665  4.007553e-01  1.7706344720  0.6363477528
##   [69,]  0.6947496179  0.510536250 -1.446082e-01 -0.2643525669  1.2634613010
##   [70,]  1.4489231601  0.738047777  8.258743e-01  0.4002573771 -0.2994228585
##   [71,]  0.4225248008  0.316292955  5.791427e-01  1.0533660177  0.6479621999
##   [72,]  1.7960316939  0.162160894  5.925282e-01  1.3187284721  0.2105608962
##   [73,]  3.0298477692  0.890659873 -1.186637e-01  2.1320559799  0.6036442936
##   [74,]  0.0455855013  2.197921275  1.481407e-01  0.6127815763  0.4942808231
##   [75,]  1.4094609301  0.102032025  1.394383e+00  0.7296115777  1.5765508001
##   [76,]  0.6064976763  0.283544579  3.797731e-01  1.0521411404  0.6899377809
##   [77,]  0.2726483427  0.849902463  2.656451e+00  3.6480425247  1.6256431909
##   [78,]  0.6962138966  0.483034002  5.788474e-01  4.2471720669  4.6497386485
##   [79,]  0.8389128851  2.926245370  1.648165e-01  8.9355646361  1.4426876762
##   [80,]  1.0456418938  0.069066634  5.851353e-02  0.2535662315  0.5985514292
##   [81,]  1.5489131207  0.568009307  2.109596e-01  0.0474800009 -0.2273341628
##   [82,]  1.4582426407  0.614536301  7.694590e-01  0.8398461388  2.4541147023
##   [83,]  0.1951337553  0.843426282  1.360034e+00  0.0642298783 -0.1730038390
##   [84,]  0.5415694303  0.744433915  1.903409e-01  0.7234353173  0.4779403117
##   [85,]  0.4382621252  2.034281402  6.410049e-01  2.2558561992  1.9304612530
##   [86,]  2.3999960908 -0.021289708  1.308885e+00  1.0515378314 -0.1743539816
##   [87,]  1.5569639194  0.528956151  3.224858e-01  3.8543273553  0.1348226442
##   [88,]  1.4845221649  0.846569223  3.091739e-02  0.1517813780 -0.0287578613
##   [89,]  0.6781773382  0.109940620  1.783809e+00  0.4041950461  0.1525741671
##   [90,] -0.2655877112  0.845316741  3.299398e+00  0.4801381131  1.8231511026
##   [91,]  0.6991732837  0.418895827  1.371114e+00  0.2553012709  0.6362635935
##   [92,]  1.2856228017  0.225873189  1.547198e-01  0.4028114763  0.6430519686
##   [93,]  1.4630849761  2.157918602  1.028454e+00  2.2426258660  1.1146115846
##   [94,]  2.6060763987  0.072254992  2.575910e-02  0.4382050876  0.9842497435
##   [95,]  2.0829244047  2.805385609  8.056034e-01  3.5496650694  1.7706903020
##   [96,]  0.2717641586  0.363189290  1.338850e+00  0.6813698014  0.6544558634
##   [97,]  0.7734654696  1.457221694  4.721913e-01  0.4385434463  2.7124382699
##   [98,]  1.1021849182  2.194363271  5.009698e-02  0.3058867382  0.0788345977
##   [99,]  2.6847810203  0.074476080  3.029940e+00  1.2548288970  1.3510557997
##  [100,] -0.0027534466 -0.143128258  1.602313e-01  1.0150069491  0.2134898496
##  [101,]  1.0607218068  0.609544012  2.457055e+00  0.6638469351  1.0345938349
##  [102,]  0.8979810632  1.540026776  7.086216e-01  5.0973144989 -0.0980141629
##  [103,]  1.4872551248  5.201781521 -3.456841e-01  2.2378695874  0.1218403664
##  [104,]  0.8750774785 -0.036488284  5.193587e-01  2.3378226677  2.2181861198
##  [105,]  0.6384261054  3.587952138  5.974466e-01  0.6719077962  0.6454797922
##  [106,] -0.1677394614  0.748442395  4.472943e-01  1.6985829725 -0.0850553106
##  [107,] -0.0883495139  0.340250613  7.213549e-01 -0.0665518300  2.9287154783
##  [108,]  0.1983507588  0.520396983  1.384545e+00  4.7504779517  1.8120008551
##  [109,]  0.4532336968  5.606624000  2.252682e+00 -0.1208701227  3.5300957877
##  [110,]  2.5236232771  2.920293902  3.160425e+00  0.1512612865  0.8066473992
##  [111,]  0.3253896404  2.204260720  9.476556e-01  0.7877077875  0.1160330320
##  [112,]  0.9380477449  0.776030019  2.566891e-01  0.3964156080  2.0753533039
##  [113,]  1.5104597247  5.105493867  7.366431e+00  1.9225545301  0.5453990632
##  [114,]  0.1011603516  0.535432886  2.680812e+00  1.1398797233  0.2566259157
##  [115,]  0.1299373842  0.818155785  1.106181e+00  1.0149313860 -0.1865709301
##  [116,]  1.4409492275  3.012617723  8.539139e-01 -0.4538665288  1.0979173553
##  [117,]  2.6336535642  1.088436207  1.066137e+00  0.5921617749 -0.2195233076
##  [118,]  3.7544366570  0.796461293  1.953726e+00  1.1618622727  1.0403330429
##  [119,] -0.1061752389  0.466593247  1.881987e+00  0.1316096238  1.4927098112
##  [120,]  7.0296091730  0.448276110  8.875708e-01  0.7184856174 -0.1803374651
##  [121,]  0.0794855665  1.230300041  2.684549e-01  0.1484920550  0.6287912862
##  [122,]  8.0526261954  2.816223458  6.968523e-01  1.0336744006  0.3658222302
##  [123,]  0.1306233818  1.906839931  7.779904e-01  0.2437511068  0.0615054258
##  [124,] -0.3431438115 -0.235951707  3.178911e-01  2.5072702741  5.4264163584
##  [125,]  0.0725784289  0.168712252  1.190574e+00  1.9430368657  0.5637843004
##  [126,]  1.7337671525  2.026732760  2.267638e+00  0.5638456767  1.7180677527
##  [127,]  0.0204958652  0.438860582  8.816541e-02  4.9148495754  0.3178439736
##  [128,]  0.5809347927  0.425986617  2.081296e-01  1.1801434044 -0.0372437468
##  [129,]  3.1309807334  0.018966713  1.117206e+00  0.1706629828  0.0026468015
##  [130,]  1.3272389544  2.204378207  2.174068e+00  0.2541562154  1.9974707247
##  [131,]  0.0559067196 -0.107085528  3.472043e+00  0.9362365168  0.2341256393
##  [132,]  0.2608457264  1.221056700  1.605398e+00  3.9541708115  0.5109829493
##  [133,]  0.7578896415  0.245907473  1.253497e+00  0.1855813470 -0.1602069968
##  [134,]  1.4230443535  0.807536989  3.179253e+00  0.4773601447  0.5725133395
##  [135,]  0.6505713649  4.739982306  1.348432e+00  0.8866622531  0.0804743260
##  [136,]  0.2544003353  0.296419552  1.315000e+00  0.0904545822  0.1506691369
##  [137,]  0.6848302513  0.543905277 -6.795872e-02  0.2792654857  0.2060893227
##  [138,]  1.8915115606  1.323661166 -2.385787e-01  0.3284517524  2.2083740793
##  [139,]  1.6781346724 -0.211207906  3.001526e-01  0.5860791538 -0.2032686298
##  [140,]  0.7577611939  1.271970529  2.801854e-01 -0.0176678764  4.6534657022
##  [141,]  3.1874074620  0.099496678  6.367017e+00  0.9252066685  0.1018462678
##  [142,]  4.0080488283  0.437903681  9.648877e-01  0.0669583609  0.7720577041
##  [143,]  0.6082740646  0.964153371  2.509988e+00  2.4875685523  6.6522775541
##  [144,] -0.0044581244  1.310275024  5.991592e-01  3.4371340444 -0.0480982244
##  [145,]  0.3502236561  6.913794868  2.485816e+00  0.9859569818  1.1060067811
##  [146,]  4.1122461227  0.728989349  8.953880e-01  0.3117000675  3.0550443320
##  [147,]  0.3583031498  0.411269705  1.169996e-02  0.6040332243  0.4910508709
##  [148,]  0.0029454601  0.256259330  3.504142e-01  0.9262784551  0.5355918977
##  [149,]  0.1291345622  0.410555259  1.147914e-01  1.6939883259  0.7263829137
##  [150,] -0.1654568641  0.914908671  1.134652e-01  0.1081865113  2.4172959811
##  [151,]  1.2398693989  0.361939474  3.199659e+00  0.8747277274  0.1569737857
##  [152,]  3.2405638836  0.655857125  1.388283e+00  1.0923718747  0.9014946991
##  [153,]  1.2113814843  0.042284840  1.010004e+00  0.2829558659  0.7415751533
##  [154,]  0.3908059392  2.162129309  2.487945e+00  2.4737999469  1.4223973544
##  [155,] -0.0689702823  1.099215902  1.987157e+00  1.0819583166 -0.0473050753
##  [156,]  0.9842864762  0.548100312  2.288121e+00  1.1992366825  1.9856048012
##  [157,]  0.0151521277  0.677302103  4.067275e+00  3.7357734525  1.9022511931
##  [158,]  6.5592316842  0.626781128 -2.762948e-01  1.4584597986 -0.2472861638
##  [159,]  1.2611620545  1.910949633  1.811207e-01  0.4823601061  1.6675741662
##  [160,]  1.5263898729  0.896658275  1.048544e+00 -0.3160325273  0.0676947886
##  [161,]  0.8058465462  0.479681045  2.219043e+00  0.7125312653  0.0313326241
##  [162,]  1.9393240384  0.492580729  3.428450e+00  0.3065151859  2.0389196013
##  [163,]  1.1921341498  1.132459593  9.354157e-01  2.4798516329  1.2004851359
##  [164,]  1.4356877114 -0.063113466  1.052363e+00  1.7560490430  1.7201203911
##  [165,]  0.1866128377  0.658596504  6.710839e-01  4.4874252945  1.3524248017
##  [166,]  0.0973286144  0.045050729  3.697134e-02  1.2266826409  0.6915835989
##  [167,]  0.0764357071  0.576885986 -2.915317e-02  0.1059033711  0.3555598697
##  [168,]  0.2690648084  0.716768363  1.291449e+00  2.1122524815  0.9500321941
##  [169,]  0.1221142542  2.994615288  2.585714e+00  0.2228179047  0.5931524701
##  [170,]  0.1220807650  1.341488400 -1.427029e-01  0.2090994249  0.2472110477
##  [171,]  0.0824181485  0.921995498  5.273180e-01  1.8135915759  0.6815956027
##  [172,]  0.7794914041  0.095906858  1.224707e+00  0.2008484376 -0.0199153714
##  [173,]  0.7419444876  0.277312846  8.818480e-01  1.1034887726  1.5767721109
##  [174,]  0.5256416408 -0.431145822  1.516616e+00  1.2316603850  0.3337436938
##  [175,]  0.7458272278  1.300805400  9.093415e-01  0.1955291520  0.6519026940
##  [176,]  0.1555165883  0.136607798 -2.396751e-01  0.6891947452 -0.1469955942
##  [177,]  0.6717522349  0.179465781  9.341815e-01  0.8287703978  0.6233574234
##  [178,]  1.2197789433  2.060789367  2.776752e-02 -0.2743954713  0.2274071165
##  [179,]  2.1756176611  2.762943500  9.066430e-01  0.9382941907  2.4511629875
##  [180,]  1.0132653802  0.300244669  1.707847e-01  1.6870668665  1.1960654026
##  [181,]  0.8997965128  0.349841591  4.098656e-01  3.0327441927  0.3820418510
##  [182,]  0.2833990746  6.111539242  1.371659e+00  1.5730689076  0.6621881026
##  [183,]  0.0578935963  0.978759644  5.827046e-01  0.4001392989  1.4197949920
##  [184,]  4.0926388887  1.556992684 -2.910024e-02  3.3049696841  2.5592560379
##  [185,] -0.4210950260  2.032133333  1.457556e+00  2.5583085815  0.6838911767
##  [186,]  0.2244961697  0.443712868  1.149166e+00  0.0861599440  1.1969974241
##  [187,]  0.4494716984  1.682385889 -5.945079e-02  0.6089616376 -0.1097801619
##  [188,]  2.0084320634  3.093718062  1.384535e+00  1.1810638257  0.9071996389
##  [189,]  0.4404703204  0.740101637  7.992099e-03  2.1267422391  2.5824331989
##  [190,] -0.1194730411  0.035533630  1.492116e+00 -0.0631059364  0.3053694912
##  [191,]  1.0328783711  0.587408937 -1.614729e-01  0.1827031999  4.5954589701
##  [192,]  0.8835096641  0.579109081  1.557394e-01  0.3671332044  1.7308669639
##  [193,]  0.8528553440  0.154788120  3.370801e-01  0.9484153805  0.6492562108
##  [194,]  0.2812343743  0.170921026  2.614060e-01  0.1029831615  1.0297260905
##  [195,] -0.0667187324  0.211474393  4.513691e-01  0.4186830584  0.0668228371
##  [196,]  0.4321752753  3.733896362  1.825514e+00  2.7139007466  1.3882746363
##  [197,]  0.3999594885  0.966433646  1.239728e+00  0.6696736636  0.5185900792
##  [198,]  0.2736208770  0.132307263  2.421068e-01  0.1533490153  1.2380211236
##  [199,]  3.0237796408  0.384407163  4.449479e-01  0.1794092502  1.4926731853
##  [200,]  1.1910231276 -0.069174220  2.189580e+00  0.0067855161  1.8823572721
##  [201,]  1.2015267629  4.076701169  2.224596e+00  1.4076137508  1.5294466065
##  [202,]  0.5071927331  0.809470680  3.231863e-01  0.1088824492  0.2121236932
##  [203,] -0.0361936369  1.172328684  1.127662e+00  0.7196752709  0.3841508761
##  [204,]  1.5882427725  0.411914804  4.663373e+00  2.1254544522 -0.2457628471
##  [205,]  0.2165562694  2.990101270  1.911130e-02  0.5095735696  2.6024708018
##  [206,]  1.1906306170  3.711108961  4.902151e-01  2.0773575774  0.2793070756
##  [207,]  0.5801082713  0.787259517  1.670499e+00  1.0925867304  0.6841392921
##  [208,]  1.9762391384  0.849736103  1.540902e+00  0.0096533272  0.9060167670
##  [209,]  0.3349952586 -0.028548144 -2.532726e-01  0.5816419138  1.2511026650
##  [210,]  1.1926396419 -0.236055614  9.788991e-01 -0.0840359930  0.7279507072
##  [211,]  0.4303752661  0.919588552  7.508309e-01  0.4394327047  0.4930760271
##  [212,]  1.5136451493  0.521022167  2.980220e-01  0.7899199800  1.2290282734
##  [213,] -0.1422095083  0.240879019  2.232604e-01  0.8810589331  0.1699514524
##  [214,] -0.1463587622  0.479490547  1.069341e+00  0.0003908356  0.2087575372
##  [215,] -0.4614416592  0.667796655 -1.039786e-01  2.3222392153  0.6031021284
##  [216,]  2.0202880626  0.616873855  1.104919e+00  0.8036008374  0.5209807538
##  [217,]  0.3780280139  0.055757612  1.040766e+00 -0.0605769588  1.9784005130
##  [218,]  1.7848417962 -0.457256442  1.806492e+00 -0.0732936204  0.9942754355
##  [219,]  1.8761062191  0.871027681  5.527348e-01  0.1579664499  0.0503862620
##  [220,]  0.1556850814  0.127598877  1.986860e+00  0.9716741273  0.4101924373
##  [221,]  0.1058842430  1.563172884  4.727202e-01  0.4355941553  0.3215380208
##  [222,]  0.3514534318  0.295893550 -1.630300e-01  6.6495033560  1.8912336715
##  [223,]  0.3498713906  0.781062774  2.670079e-01  0.0012203309  0.2041387822
##  [224,]  1.0639740889 -0.258737030  4.622039e-01 -0.2800515095  2.0397525128
##  [225,]  2.0827447650  2.441912523  2.308956e-01  0.7716640005  0.2766041706
##  [226,]  0.4340685920  2.308898515  1.849197e+00  1.9121576461  1.4742894842
##  [227,]  0.1952658587 -0.097463142  2.060476e+00  1.2555975637  0.6057057573
##  [228,]  0.8246007798  0.306040901  1.084928e-01  0.2258123567  0.9756046918
##  [229,]  0.5548949343  0.458699135  4.384611e-01  0.8586548160  1.0556149659
##  [230,] -0.0044906501  1.486921261  5.504465e-01 -0.3145071831  0.3964569311
##  [231,]  1.2073840371  1.584158361 -1.504269e-02 -0.0863809876 -0.3165187899
##  [232,] -0.0769197723  1.305497734  6.445819e-01  4.0289490098  2.6977383509
##  [233,]  4.6003136347 -0.130373284  6.456291e-01  3.4684785813  0.2779797406
##  [234,]  2.9705310186  3.224047747  5.914493e-02  5.1095599982 -0.1980321277
##  [235,]  0.1112249684  2.885987864  3.198790e+00  0.6275800152  0.0129513905
##  [236,]  0.7666647327  1.439261538  1.761867e+00 -0.0601920191  1.3632112873
##  [237,]  0.0930342303  0.374721464  6.468697e-01 -0.0218150805  1.1042690301
##  [238,]  0.6781814609  0.263812176  1.304911e-01 -0.0433276465  5.3921120371
##  [239,]  0.1303217147  0.389251802  1.781287e+00  1.2328181533  2.4839084242
##  [240,]  2.2439918973  0.126785393  1.506059e+00 -0.2508053815  0.6343646861
##  [241,]  1.8573241062  0.258880553  3.782298e-01  3.3519381394  0.8255925958
##  [242,]  1.0625954769  1.186594175  7.785985e+00  1.5541523218  0.1501478208
##  [243,]  1.2799929700 -0.283437470  2.324880e+00  1.7583411117  0.5801087119
##  [244,]  4.2642658402  3.394614120 -1.060725e-01  0.0243533507  1.4177216508
##  [245,]  0.9616128434 -0.082121890  4.086588e-01  1.3678343501  1.6399824214
##  [246,]  0.0008041398  0.333901662  3.265088e+00  0.3863576280 -0.0672566135
##  [247,]  2.8394664273  0.943614871  9.795063e-01  1.4810853067  0.3651707673
##  [248,]  0.5647755943  0.807276589  3.026744e-01  0.4248331460  0.3492738120
##  [249,]  0.1937327542  1.316394204  9.166358e-02  0.4777363921  0.3242786001
##  [250,]  0.0408596512  0.566474778  6.297263e-01  1.1560461608  2.8570711653
##  [251,]  2.2245054709  2.639843575 -9.177643e-03  0.5006719123  1.1612070434
##  [252,]  4.3152040156  1.276334597  2.776061e+00  0.3095337846  1.4159214488
##  [253,]  1.2789027440  1.727963115  2.111424e+00  1.9804999382  0.1626771715
##  [254,]  2.0598227380  0.057711567  3.637848e-02 -0.1584039342  0.8799483271
##  [255,]  0.1560410582  0.187643397  4.959399e-01  0.3738968625  1.0900036864
##  [256,]  0.3825448419  0.133942401  1.523994e+00  4.5275326560  1.3492384472
##  [257,]  0.5373720323  0.571788273  2.491099e+00  2.5399007685  1.5695660623
##  [258,]  0.0113356927  2.000786043 -1.417921e-01  0.7817817588  0.4235688432
##  [259,]  0.2543749426 -0.137774756  2.655785e-01  0.8893277548 -0.0123139236
##  [260,]  0.1762645512  2.306854911  2.296156e+00  0.0016829407  0.0639483051
##  [261,]  0.6789261466  0.680212008  1.520525e-01  0.7418353045 -0.2193473280
##  [262,]  0.4549488004  0.715802295  6.422778e-01  1.1532310171  1.3315899439
##  [263,]  0.7257707812  1.077422694  1.021549e+00  1.9484416777  0.4589386066
##  [264,]  2.2137615915  0.015312211  4.693887e-01  1.5746087712  0.5874071909
##  [265,]  0.9608862844  0.225146150  5.697055e-01  0.6393947670  0.1241026140
##  [266,] -0.0119519002  0.787053791  2.739645e+00  1.0961839339  0.8263611914
##  [267,]  0.4526522472  0.675035784  3.201631e-01  2.9023168484  1.4315483895
##  [268,]  1.2292726068  0.442575921  1.455888e+00  0.1568333599  0.5070280402
##  [269,]  0.1629255077  3.076476645  2.011952e+00  0.2666340762  0.9710574054
##  [270,]  0.4961546815  1.299631698  1.283053e+00  2.3607353564 -0.0936393901
##  [271,]  1.2057981256  2.004976953  1.267886e+00  0.1473423907  0.8309420369
##  [272,] -0.0810033704  1.090945667  9.023816e-02  0.3890603941  2.1198732838
##  [273,]  1.1774174378  0.425204443  4.477531e-01  1.9386047349  1.1098245044
##  [274,]  0.5750727374  0.656209675  6.988344e-01  0.6293466542  2.0240419276
##  [275,]  1.3519725749  1.546397675 -3.203979e-01  3.4564486201 -0.1150940078
##  [276,] -0.1182505759  1.073615874  8.286356e-01  0.9279667649  1.6664911215
##  [277,]  0.2913076508  2.430978890  5.870048e-01 -0.0973692554  1.9233207068
##  [278,] -0.0749902025  0.285751154  8.571941e-01  0.3724765325  3.4510552450
##  [279,]  0.5873635145  0.330341766  2.755992e-01  3.6333392237  1.7388802767
##  [280,]  1.4318601326  0.307496658  1.649754e-01  0.9442813654 -0.1239723384
##  [281,]  0.6725643902  1.718532562  1.428300e-01 -0.0136390015  1.0019733927
##  [282,]  0.3344317747  0.541170035  9.292772e-01  2.8253850179  0.3996384141
##  [283,]  0.2489827293  0.759483759 -6.417865e-02  0.1223195282  1.1927794117
##  [284,]  0.6220232802  0.212505828  4.508285e+00  2.1157899784  2.3023091332
##  [285,]  1.1713752449  0.148741755  4.149997e-01  0.2744163706  3.9063918698
##  [286,]  0.7020393591  4.391192934  1.707428e+00  0.7373841361  1.3114956676
##  [287,]  0.3923743912 -0.278049985  1.692437e+00  2.0890600766  2.6960959297
##  [288,]  2.9751293631  2.944097397  2.110887e-01  2.1213991743  2.1411497316
##  [289,]  0.2514718183  0.248301787  5.260288e-01  0.3632210106  3.6040298325
##  [290,]  1.9603027753  0.961243068  1.936118e+00  2.1051382293  0.2668879095
##  [291,]  1.9142373502  0.598123000 -9.158919e-02  1.2336568299  2.4937298428
##  [292,]  0.2349569687  7.006040154  5.791917e-03  1.2259496859  0.7038091482
##  [293,]  1.3836064106  1.721958569  5.497390e-01  0.4130085328 -0.0271764005
##  [294,]  0.7947043983  0.267111441  4.726707e-01  0.3394460938  1.4676073910
##  [295,] -0.5023812141  0.725550582  3.212466e-01  2.0718765129  1.5186623001
##  [296,]  0.4572061742  1.766479422  7.247581e-02  5.1256206022  0.1712839240
##  [297,]  2.8633670894  0.518657485  1.014833e-02  3.0796160621  1.0394422348
##  [298,] -0.0519110129  0.179469562  1.381244e+00  0.0274526772  1.7135854953
##  [299,] -0.0815798296 -0.090266922  6.208417e-01  0.3641931380  0.0642098814
##  [300,]  2.4085485980  0.399307565  2.625961e-01  1.4949930258  1.3060413009
##  [301,]  0.7359863386  1.959244262  6.774258e-01  0.4797127694  0.3026553756
##  [302,]  2.2231011072  0.308311742  9.706646e-01  1.1994571309  0.4824754605
##  [303,]  0.5642388458  3.522298550  1.429358e+00  0.2793157350  1.2793197858
##  [304,] -0.3546309579  3.482176581  6.679781e-01  0.4612061684  0.7676147837
##  [305,]  1.1129068342  0.353033084  1.030680e+00 -0.3652619148  6.6516446261
##  [306,] -0.1815540895  0.569096297  6.108017e-01  1.0886593405  0.2838775187
##  [307,]  1.5132484344  0.280277627  3.995168e-01  1.8025544908  0.5562438524
##  [308,]  1.7388229095  0.806642921  1.347682e+00  0.4810773191  0.7649920678
##  [309,]  0.6683715258  1.909842956  1.048546e+00  1.8843371364  0.2523875637
##  [310,]  0.2850278170  0.465377949  1.690433e-01  1.2977879867  0.9244487185
##  [311,] -0.1574710554  0.314470814  9.990950e-01  1.5536545185 -0.1222338935
##  [312,] -0.2049128432  4.533803801  2.877967e-01  0.9813328056  0.5130242584
##  [313,] -0.0264882787  0.605153874  1.773715e+00  1.6944043485  0.0682998015
##  [314,]  0.3455653119  1.156976081  3.158690e-01  0.6916431255  0.6203046121
##  [315,] -0.1859176283  1.902891655  8.370801e-01  0.0444365695  0.5938417016
##  [316,]  0.0148063528  0.936498733  5.434381e+00  0.2468168983  0.4163329486
##  [317,]  1.7520137403  1.527290842  6.902908e+00  1.4229456515  1.1621468087
##  [318,]  1.9502451957  1.839593655  1.025533e+00  0.0378984801  0.1946419797
##  [319,]  1.0658260277  0.233257995  1.023145e+00  0.1563133159  0.0611961755
##  [320,] -0.4661292628  0.115480138  2.637133e-01  1.6160648655  0.4226433596
##  [321,] -0.3803564803  2.492523293  1.867027e+00  0.7954369112  0.1434740830
##  [322,]  0.2153738343  0.119064065  7.253491e-01  2.1388255980  0.1054024832
##  [323,]  0.5992527583  0.198535391  4.563825e-01  0.3512953169  0.3276608480
##  [324,]  0.6287889590  0.647699320  5.246603e-02  0.6706892552  1.8610003519
##  [325,]  1.1930871651  2.455683417  4.337806e-01  1.1695197870  1.4953321299
##  [326,]  1.0376363997  0.572191738  2.387830e+00  0.3573826683  0.0666523540
##  [327,]  0.1953189393  3.831065900 -2.565085e-01  4.0831818750  1.1615183315
##  [328,]  1.3376425559  1.651298131  2.772032e+00  2.0207557399  1.2671000945
##  [329,]  1.4755941834  0.306389790  7.148262e-01  2.6017698374  3.3026589736
##  [330,]  0.2675003072 -0.129396392  2.796231e+00 -0.0941049918 -0.2708846440
##  [331,]  0.6275202402  0.602010967  5.979681e-01  1.3836759105  3.9832043206
##  [332,]  0.4968479621  0.701949937  1.654207e+00  0.0456713002 -0.2996000381
##  [333,] -0.1621415581  1.159046081  2.023156e+00  0.3525566192  0.5173168935
##  [334,]  1.3860186673  0.016088843  2.033913e+00  0.8400574595  0.5519324286
##  [335,]  1.0537034086 -0.076229832  9.981447e-01  0.0512929000  1.8194876506
##  [336,]  0.3320877122  0.588092122  1.514640e-01  0.8791586176  0.7720866963
##  [337,]  0.6614760637  0.469618747  1.485871e+00  1.2791001898  0.9629969190
##  [338,]  1.3034059143  1.148277117  2.876474e-01  4.2333529491  2.6179364098
##  [339,]  1.0559144365  2.023976832  8.400320e-01 -0.1108229441  0.2520467143
##  [340,]  0.1723085348  1.333921804  2.813459e+00  0.4337470555  0.5017667353
##  [341,]  0.7491424813  0.011432678 -2.944631e-02  0.6931463143  0.4825902600
##  [342,]  1.5523104452  0.034093485  2.380479e-01  1.2264371207  0.8902368302
##  [343,]  0.3060939676  2.616918575  1.389800e+00  0.5331781889  0.6988677550
##  [344,]  0.9625413438 -0.270020302 -1.215348e-01  0.0202602986  0.0498760963
##  [345,]  0.0789288442  1.805667260  1.421844e+00  2.3055732679  0.1321692292
##  [346,]  0.5448635516  3.237982262  3.022944e+00  1.0913469567  0.3510885955
##  [347,]  0.1582822460  1.281371382  5.122135e+00  0.2277751434  0.3498221778
##  [348,]  0.5106397821  0.528654815  1.743445e+00  0.4364988043  0.4511061687
##  [349,]  0.1234711143  0.162545213  9.438965e-01  0.1060653873  0.2615316527
##  [350,]  0.1680042007  0.050797186  3.943515e-01  0.0328468976  1.4030784337
##  [351,]  2.2605138043  1.868483129  1.352672e-01  0.9783662466  0.8385302022
##  [352,]  0.0711624916  0.138332963  8.009335e-01  1.0262092620  0.4974795808
##  [353,]  0.8503000259  1.735048095  4.514415e-01  1.0650883567  0.8030142493
##  [354,]  0.1389887871 -0.146774797  1.924995e+00  1.1157203600  0.2024826856
##  [355,]  8.5491160041 -0.456786419  5.449526e+00  1.0043243808  1.3294630612
##  [356,] -0.0960363767  0.095854653  1.887799e-01  0.1863826814  0.4258084969
##  [357,]  0.6557912896  1.193845282  1.512066e+00  0.6873511447  5.0027486029
##  [358,] -0.0324505483 -0.183858173  1.197567e+00  1.8889082685  2.0402537028
##  [359,]  0.5756151478  0.167053643  4.549597e-01  0.8737279650  0.1101804767
##  [360,]  1.7534884324 -0.106011562  7.724322e-01  0.1388171203  0.1462442287
##  [361,]  0.1561076223  2.208229293  1.295372e+00  0.2311123410  0.0763653983
##  [362,]  0.0563668019  0.282068880  2.386529e+00  0.3362933861  0.2554173660
##  [363,]  7.5696064026  1.133404407  9.981224e-01  2.1805705840  0.9214141572
##  [364,]  1.8647373653  0.906755958  1.674385e+00  1.3547478040 -0.1239885147
##  [365,]  0.4575370742  0.287958283  8.985130e-01  0.1542815105  0.2734012068
##  [366,]  0.4247035636  1.740594815  2.032064e-01  0.5409728238  1.3936807942
##  [367,]  0.8731807682  0.355496067  1.567566e-02  0.4501593183 -0.0484389826
##  [368,]  0.3155003780  1.814093553  4.204605e+00  0.7438910837  0.0186663022
##  [369,]  0.6211255524 -0.105625137  1.857883e+00  0.0644440678  0.6045619310
##  [370,]  1.3063398633  0.409498970  2.595242e-01 -0.1109765815  1.4951572466
##  [371,]  0.6016862058  1.082708534  7.795831e-01  0.3113869483  1.0907464998
##  [372,]  0.9434966108  2.663919221  1.020285e+00  1.3642496940  0.2125379712
##  [373,]  0.6171107832  0.542998731  2.335446e-01  0.6434352130  2.4266144619
##  [374,]  0.1496199970  0.261767750  1.939915e-01  0.3535407453  0.4670180048
##  [375,]  0.3362505183  0.281965321  5.291053e-01  0.6871617112 -0.2342493227
##  [376,]  1.1060789291 -0.100705906  2.564294e-01  0.3965467176  0.7956068747
##  [377,]  2.2514916235  1.475987396 -3.557647e-01 -0.0184483367  2.9966714302
##  [378,]  0.4249538359  3.014695483  5.736487e-01  0.3541578510  2.7644786379
##  [379,] -0.2120987730  2.935701924  7.318352e-01  1.2154531718  0.0722767905
##  [380,]  1.5148861281  0.776542974  6.122713e-01  0.3386555421  1.6973141231
##  [381,]  1.3208486571  1.267732517  3.375141e-01  0.1237865605  0.5922047035
##  [382,]  0.4698242766  0.146611895  2.373671e-01  0.6111291332  1.5976230987
##  [383,]  0.6566407082  9.079625205  7.562181e-01  0.3956392852  0.2509180381
##  [384,] -0.0301825605  2.967423309 -5.966398e-02  1.7015069021 -0.2224893540
##  [385,]  0.2951933493  0.453595649  1.033363e+00  4.1779102346  0.3797464038
##  [386,]  0.7772181887  3.997049564  7.009737e-01  0.9536751628  0.3698275381
##  [387,]  1.6778761125  1.326958892  2.440406e-01 -0.2394412716  4.2547200891
##  [388,]  1.3117111205  0.014010716  1.084661e-01  0.5574849110  0.2695056989
##  [389,]  0.1119187149  1.575003583 -1.599236e-01  1.0146579590  0.8515102282
##  [390,]  1.2816179824  0.819728254  7.147531e-01 -0.3373262114  0.0008125804
##  [391,] -0.1093804008  1.142957441 -1.225801e-01  3.6007678524  0.4170586453
##  [392,]  0.0567673381  1.848877541  1.250660e+00  0.9354863105  0.7177815621
##  [393,]  1.0396103857  1.172860996  5.193587e+00  0.4271076228  1.0133350311
##  [394,]  0.6301105972  1.023007772  6.035862e-01  1.5549320106  6.0587658471
##  [395,]  0.2966881160  0.004190942  1.847370e+00  0.2552193996  0.8841211648
##  [396,]  0.2921842069  0.815444474  1.987768e+00  0.2548957461  1.2866289118
##  [397,]  1.1288775445  0.696988655  1.219319e+00  1.5301899562  0.2116760447
##  [398,]  0.1755406761 -0.103848244  2.460770e-01  0.8165468944  0.8481443572
##  [399,]  2.9065510750  2.651165900  1.917795e+00  0.1255669798  1.0460928596
##  [400,] -0.2164039161  0.118319298 -2.157310e-01  1.5960987085  1.4220697463
##  [401,]  0.1357501175  0.296229302  4.974282e-03  2.6932799671  0.2023290120
##  [402,]  0.5223144481  0.103146703  9.550306e-01  0.1208306191  0.4047732589
##  [403,]  0.3449082225 -0.158966015  4.968142e-01  0.9346582716  0.5491341790
##  [404,]  0.8213786962  0.696709307  2.221067e-01  0.2453823459  0.2181463453
##  [405,]  0.6884716953  0.289202754  1.471622e-01  2.4056666907  0.2720865853
##  [406,]  0.0235009665  0.168924080  3.651230e+00  0.1196485160 -0.0044228034
##  [407,]  5.4682056908  4.192125468  1.769932e+00  2.0018667664  1.6341912864
##  [408,]  1.6253085227  1.442847590  1.543029e+00  0.9586597794  1.7559650652
##  [409,]  0.4885518102  0.028973810  1.426164e+00  2.1061381908  0.4434718424
##  [410,] -0.1788756358  0.699588205  3.535820e-02  1.5100716082  0.8091125107
##  [411,]  0.2871669015  1.787232722  3.109351e-03  1.6821631590  1.4060241496
##  [412,]  1.3001470570  0.448476030 -1.762857e-01  0.1199815151  1.2261868360
##  [413,]  1.1740653590  2.312270861 -2.000794e-01  1.6370409476  1.0399541696
##  [414,]  1.1844389577  1.778484241  1.255942e+00  1.6959058944  1.8388478506
##  [415,]  0.5790943752  0.668830841  2.315033e+00  0.1500232644  0.2263520025
##  [416,]  0.0903990834  0.393023754  4.338760e-01  0.0009509438  0.2577780559
##  [417,]  3.0973376259  0.734366596  3.532025e+00  0.4301789875  0.4183038809
##  [418,]  0.0972411122  0.871392566  4.040766e-01  0.9030268461  3.2964327590
##  [419,]  3.1841355329 -0.018848477  2.140488e-02  0.6487191169  1.3864527362
##  [420,]  0.7552868391  0.191949287  6.148812e-01  1.3344914721  0.7791235691
##  [421,]  0.2381593751  0.192728885  4.958179e-01  4.2269736913  1.0793881047
##  [422,]  0.6264004411  1.862698713  7.797778e-01 -0.0446398431  0.3789076178
##  [423,]  0.0626742923 -0.163989807  4.054137e-06  0.0679697578  0.0840930998
##  [424,]  0.4727419080 -0.085166630  3.316193e-01  1.1452567060  0.7139049066
##  [425,]  0.8144562387  1.787086114  7.438359e-01  4.4998407928  0.1880227853
##  [426,]  0.6065300609  0.462118718  1.129382e-01 -0.0762627095  2.1026101162
##  [427,]  0.9010054779  1.792875623  3.052527e-01  0.9559421667  0.5643194943
##  [428,]  0.2826084438 -0.104031235 -9.891324e-02  1.2352316674  0.4925807433
##  [429,]  3.0541115743  1.707328248  2.602467e+00  0.5464859965  0.5313533977
##  [430,]  0.1850657432  0.873580412  1.516239e+00  1.3900255748  0.0845535556
##  [431,]  0.0396456453 -0.264243287  2.278696e-01  1.2588377372  0.2239040193
##  [432,]  0.5219722297  0.293891137  1.460393e+00  0.1549047816  3.2926436110
##  [433,]  1.6953973910  1.355651395  2.268850e+00  3.5176369997  0.2233855809
##  [434,]  1.7371086451  2.006518142  1.515464e+00  2.0551730751  3.0721514141
##  [435,]  0.5093117926  2.455152579  5.319956e-01  0.2669149437 -0.1854077140
##  [436,]  0.2847078404  0.421737859 -7.084179e-02  1.0918808189  2.7895049928
##  [437,]  0.7367161584  2.136630637  9.891777e-01 -0.0068974138  0.3645235727
##  [438,]  3.4340400692  0.275151905  1.515951e+00  0.9570690067  0.8822348144
##  [439,] -0.0496864853  0.618885739  1.128176e+00  0.8793129143  2.1465938812
##  [440,]  0.5131940877  2.204966590  5.140206e+00 -0.2092847680  5.6957252701
##  [441,]  0.3077606050  0.194961317 -5.760344e-02  1.1977227998  2.4254682730
##  [442,]  4.5034019196  2.733055636  5.463613e-01  1.5369618715  1.8599196207
##  [443,]  3.0001770617 -0.140418065  1.444829e-01  1.0292879434  0.2852090007
##  [444,]  0.0655889660 -0.088687457  6.217363e-01  3.8197196304  0.0321209260
##  [445,]  0.9573571993  0.749497279  2.206152e+00  1.3495603531  1.9403203003
##  [446,]  4.3733296810  0.067953753  1.803574e+00  1.2195622066  4.0738907406
##  [447,]  0.0685515155  0.143802800  1.560658e+00  1.0716278458  0.6984105538
##  [448,]  0.7101918635  1.001000101  8.364695e-01  0.6173471020  0.3621107065
##  [449,]  1.9490844196  1.172289615  2.467734e+00  3.6774889096  0.4860980664
##  [450,]  0.6061782667  2.084748711  1.970396e+00 -0.0224316692 -0.0260577248
##  [451,]  0.2811918387  0.037559590  4.522639e+00  2.1275955545  2.1359703774
##  [452,]  1.0996469933  0.246834094  9.457690e-01  1.1358004107  0.7301427622
##  [453,]  0.4742802012  0.787726020  5.015756e-01  0.4597515893  0.6840990152
##  [454,]  1.4254816791  1.801751295  6.432443e-01  0.6759919562  0.0288258146
##  [455,]  0.3522504608  0.212092180  8.696105e-01  1.5892119302  1.1053344442
##  [456,] -0.0698023572  2.522547339  1.346917e-02  2.1092895437  0.2782975081
##  [457,]  0.2557957470  2.585883262  9.184012e-01  1.4746873230 -0.0666914474
##  [458,]  0.9715932484 -0.023955287  1.578080e-01  0.5433655156  0.3342860702
##  [459,]  1.3394770604  1.326496330  3.279673e-01  0.5109201726  0.4263319015
##  [460,]  0.9827551747  0.755936221  9.390392e-02  0.1579584623  0.1216956217
##  [461,]  0.7966977056  1.044278526  1.644729e-01  1.7177819269  0.3153429986
##  [462,]  2.2572648848 -0.038130212  1.991099e+00  0.4142499353  0.1611649228
##  [463,]  0.5371275534  0.933078072  1.162221e+00  0.4652326460  0.6732409824
##  [464,] -0.1278105587  3.230385752  4.645745e-01  0.3102647503  0.1112298696
##  [465,]  1.2838749225  0.333831332  9.556042e-01  0.0209764096  2.5567734104
##  [466,] -0.4970079853  0.936684059  1.734480e-01  1.2665365208  0.0493594340
##  [467,]  7.4304157386  0.735771620  3.207902e+00  0.5323017753  2.9914952816
##  [468,]  0.0567959855  1.039155026 -1.995607e-01  4.4956021432  0.4719498565
##  [469,]  1.0695570010  1.482876184  3.577705e-01  1.4628789964  3.6055532789
##  [470,]  3.6675563988  0.890829752 -2.232137e-01  2.1767743419  1.1639561462
##  [471,] -0.1445252786  0.169684650  4.064630e-01  0.0537583623  0.6472388080
##  [472,]  0.7212212950  0.645071581 -2.322942e-01  0.7426341581  1.3975320119
##  [473,]  0.8162906759  2.022394706  7.253271e-01  0.3756512415  2.1859609179
##  [474,]  2.9083435427  0.067755471  1.281021e+00  0.1728345911  0.9962179865
##  [475,]  1.0049317236 -0.088155728  5.214724e-01  1.0021297296  2.1945463509
##  [476,] -0.0437528132  1.721436057  2.792865e-01  2.7221810416  0.9895561539
##  [477,] -0.0219705029  0.844042166  1.516509e+00  2.4878074990  1.2537112555
##  [478,]  0.9479621431  2.280663597  2.838205e+00  1.4050175053  0.2755334919
##  [479,]  0.1607273292  0.206048106  6.189884e-01  2.7838279646  0.2633724069
##  [480,]  0.9464618224 -0.047328348 -3.763577e-01  0.0727083085  0.6003571842
##  [481,]  0.1369496035  0.329293143 -2.023572e-01  0.4333488566  0.3365728959
##  [482,]  4.6384611399  0.627439027  4.837600e-01  0.4305032375  0.5629008668
##  [483,]  2.4473469080  1.041055491  1.197084e+00  0.8791197813  0.2890677155
##  [484,]  1.0618485400  2.358318389  2.449761e+00  0.1748036083  1.0399987897
##  [485,]  2.4948005733  4.824666059  1.822946e+00 -0.2444510422  1.0920618392
##  [486,]  0.7585040896  5.224454946 -1.310682e-01  0.8692030672  0.0742351239
##  [487,] -0.0004863772 -0.268609569 -8.290662e-02  0.1349642135  0.4800972683
##  [488,]  0.7161989043  6.022625700  2.603860e+00  3.6168244570  2.3528654031
##  [489,]  1.1434076372  0.219955372  2.346305e+00  0.4840102860  0.4254640187
##  [490,]  0.8322373530  0.270466364  4.161377e-01  0.4723308505  0.2525444902
##  [491,]  1.4174675698  0.094248548  1.823345e+00 -0.1968198215  0.3613203679
##  [492,]  0.5619561399 -0.053089976  2.075746e-01  2.7963509119  0.4439397820
##  [493,]  0.5911256569  0.022133816  7.452332e-01  1.9498589378  0.0886918229
##  [494,]  1.3337293119  1.462539555  1.863152e-01  0.1226729717  0.3176128122
##  [495,]  0.1175003141  0.169951152 -5.822785e-02  0.6781233113  0.6692078318
##  [496,]  0.3853683680  0.137980520  6.560177e-01  2.3460716183  0.0748548784
##  [497,]  1.7604632230  0.471807434  1.528282e+00  0.1222301834  0.0416747233
##  [498,]  1.2588962143  0.606895968  2.943322e+00  0.7566197867  2.3484499564
##  [499,]  0.6370190935  0.476361549  6.184105e-01  1.0823950867  2.7011174859
##  [500,]  1.1273173840 -0.033745770  7.108638e-01  0.9067040605  0.0730875529
##  [501,] -0.1372415419  1.958917125  1.336747e+00  1.0545061327  0.2784646001
##  [502,]  0.6075087022  0.159986129  3.696908e+00  2.0560842004  0.0867143507
##  [503,]  0.3674932398  4.172242000  2.478431e+00  0.5778217903  1.0538543972
##  [504,] -0.1948381990  0.674875868  5.346648e-01  0.4629539234  2.0578027745
##  [505,]  3.5345522282  0.596607864 -1.134243e-01 -0.0018324847  0.8919626309
##  [506,]  0.5947788319  0.644581759  5.798953e-01  0.8661948439  0.8994166324
##  [507,]  2.6348853205  0.658148885  1.125500e+00  0.4646957799  1.0052805741
##  [508,]  0.8460490028  0.527259388  3.699463e-01  2.4729260799  0.6850268339
##  [509,]  0.2683604589 -0.462107253  1.294813e+00  1.6843192746 -0.2593773601
##  [510,]  0.7596235858  0.234835363  1.287923e+00  0.7420605314  0.5728155403
##  [511,] -0.1827179523  1.045797038  6.975737e-01 -0.1255145858  0.7205403409
##  [512,]  2.3080282386  0.094350861  3.511856e-01  2.2039776038 -0.4716642159
##  [513,]  0.2295587462  0.095719305 -1.015083e-01  0.1100331250  1.3539465615
##  [514,]  0.1100491954  0.035239818  4.063091e-01  1.3252936785  1.0468168636
##  [515,]  0.2531871440 -0.004839714  9.815800e-01 -0.0189442296  1.3053208855
##  [516,]  1.0668162186 -0.449299518  1.441318e-01  0.7198565087  0.3863294394
##  [517,]  0.4812484240  0.038122784  5.096332e-01  0.1602021833  2.3323883534
##  [518,]  2.1190343003 -0.022588202  6.364129e-01  2.7864502166  0.5344348518
##  [519,] -0.0960816996  5.489942308  3.831747e-01  2.4848161847  1.4088079805
##  [520,]  0.2382808423 -0.150549064 -4.725740e-02  0.5456703367  2.5471314661
##  [521,]  3.7470249632  0.051944182 -2.335891e-01  1.7660693282  0.2791766147
##  [522,]  2.0258437321  0.380730713  1.492397e-01  1.7433528870 -0.0610021651
##  [523,]  1.9445014044 -0.069844661  1.243275e+00 -0.0021751434  0.6350652643
##  [524,]  2.8969241888  0.319148531  1.150680e+00  2.3687612291  1.1254151501
##  [525,] -0.2492949709  0.019829507 -3.604625e-01  0.1998732057  1.0599586033
##  [526,]  1.4628354638  1.727262490  2.690925e-01  0.6588585228  0.6638846942
##  [527,]  1.5608454466  0.119214498  2.387903e+00  0.4454651465  1.5235532263
##  [528,]  2.2599638871  0.152831945 -1.570977e-01  0.4429693380  0.1459850835
##  [529,]  2.8401965851 -0.131519075  6.080097e-02  1.4485873923  3.8006971533
##  [530,]  1.3063654004  0.472685109  2.906993e+00  0.7712427776  0.6398878117
##  [531,]  1.3710140765  0.266697055  3.181566e-01  0.4236539044  2.2807971560
##  [532,]  0.9964823451  2.635925238  4.586601e-01  0.4132507275  1.5104204741
##  [533,]  0.4204107069  0.333188927  1.036512e+00  1.3634181581  1.0715072466
##  [534,]  0.0571867447  1.635285214  1.387386e+00  0.3764107645  0.2609980797
##  [535,] -0.0425671810  0.511718557  1.191640e+00  0.7809244836  0.0478987196
##  [536,]  0.6695796379  0.372915914  6.882299e-02  0.2766788816  0.4656542514
##  [537,]  0.0782641175  0.048386067 -2.085179e-01  0.2337144926  1.6720735231
##  [538,]  0.9780487487  0.762689843  2.306943e+00  2.1109591185 -0.3517375132
##  [539,]  0.1380506717  0.433552851  5.247788e-01  0.5146948260  0.0230097939
##  [540,]  0.3482793056  0.382635199  2.713038e+00 -0.2764321912  0.6196877482
##  [541,]  2.9410469680  5.731977609  9.063675e-01  3.1867805577  2.2210410078
##  [542,] -0.0413812859  0.753605866  9.058710e-02  0.2315684889  0.8682632716
##  [543,]  0.5528915075  0.938139947 -2.303234e-01  0.2101835222  1.1186164186
##  [544,]  0.1333084236  0.090883318  1.353647e-01  0.2498200893  0.8793795171
##  [545,] -0.2466310446  0.014907595  1.317587e+00  0.8807096164  3.5114060348
##  [546,] -0.0914230814  0.157935925  8.201435e-01  0.2143864591  0.5521815840
##  [547,]  0.5540899419  2.252639904  2.363315e-01  0.4937760641  0.4779570229
##  [548,]  0.0253980944  1.022739151  7.433311e-01  1.2606004412  0.1857872737
##  [549,]  0.3604550569  0.372933398  1.941820e-01  0.4197336568  0.1303547600
##  [550,]  2.4925927970  0.894490092 -2.344840e-01  3.6438316994  2.8989611011
##  [551,]  0.5280459393  0.933777106  1.235635e+00  1.2324129729 -0.3093124550
##  [552,] -0.0427840936  0.006185315 -2.137505e-01 -0.0311728312  0.3747843013
##  [553,]  0.4730345216  1.046113088  1.135548e+00  1.8255565503  0.6385611750
##  [554,]  0.4825009463  1.110139894  1.782598e+00  0.0045337108  0.2937786933
##  [555,]  0.1512916303  1.232364788  1.808328e+00  0.7855511616  0.5925819728
##  [556,]  1.5803124932  2.175570386  1.929567e+00  1.1991097588  2.2538837416
##  [557,]  0.5717096976 -0.051367285  1.461813e+00  1.0526150898  1.5443642438
##  [558,]  0.7617383885  0.611491747  1.726239e+00  0.0183083864  0.2958307367
##  [559,]  3.8542352083  0.017082713  2.277770e-02  3.0886437164  0.4810876794
##  [560,]  0.1079325717  0.332691246  2.610406e-01  0.1455363482  0.1329396392
##  [561,]  3.1426448565  1.080630569  5.155543e+00  3.3398493452  0.8539281618
##  [562,]  2.0603485923  0.265118409  4.850053e-01  1.1988138591 -0.0356418789
##  [563,]  1.4209696669  4.846623806  1.077002e+00  0.0469432417  0.8015811442
##  [564,]  0.7823720609  0.066442309  7.504015e-01  1.0882580577  0.6921626564
##  [565,]  0.3915616924  0.399635476  9.030948e+00  0.3532983086  0.1763928864
##  [566,]  1.2277941572  1.708445884  1.939774e-03  0.4124225048  0.3665453744
##  [567,]  0.1979907916  5.554167199  3.489224e+00  2.4248028244  0.0669746944
##  [568,]  4.7006031392  1.355289942  6.531982e-01  0.3263070465  1.4045314399
##  [569,]  0.8163156608  0.759498177  1.529616e-01  1.3526017610 -0.0225978491
##  [570,] -0.3712985293 -0.046772413  1.936352e+00 -0.2740929584  1.7258893039
##  [571,]  1.4036648058  0.450569676  2.644486e+00  0.2843984656  2.4493495087
##  [572,]  0.3027441699  0.270667415  4.972250e-02  2.1288061641  2.9112305365
##  [573,]  1.1309362956  0.176426130  1.712398e+00 -0.1736599798  0.5006684625
##  [574,]  0.3288808593  0.141403002  2.354183e+00  0.2932977004  0.3234055028
##  [575,]  2.7862372119  0.312850715  1.810713e+00  2.1676335163  0.2724163872
##  [576,]  0.2882093222  1.397338952  9.135795e-01  0.2580596124  1.6207237157
##  [577,]  1.7811187547  0.938338573  9.167921e-01  1.0997342100  0.4337611066
##  [578,]  1.3214237882  0.119496625 -9.110244e-03 -0.1139284172  2.4822498840
##  [579,]  0.7330639543  0.481551569  1.261396e+00  0.5156278733 -0.0738510565
##  [580,]  2.2735325260  1.114605883  5.416031e-02 11.6132244576 -0.2008199207
##  [581,]  6.9543103888  1.073968451  2.200294e+00 -0.1257036083  0.0618144722
##  [582,]  1.1822974254  0.247283182  9.924390e-01  1.0918040960  0.7935740599
##  [583,] -0.0995693938  0.768629927  5.493510e-01  3.0632470237  0.7329212994
##  [584,] -0.0217942871  0.084853876  5.303474e-01  0.7224801219  0.5250698776
##  [585,]  0.8725508275  0.179472525  9.466033e-01  0.5532721385  0.0738200812
##  [586,]  4.0221536590  1.023833568 -3.055729e-02  0.5947885167  1.2298316492
##  [587,]  0.9668673570 -0.117228694  3.405565e-01  1.2503360284  0.7146109706
##  [588,]  0.6905890660  0.413152338  6.470662e-01  0.9441649920  0.0669207310
##  [589,]  1.2745805775  0.152006113  1.081614e+00  1.3544930591  2.5631405861
##  [590,] -0.5015643218  2.472479178  1.536530e+00  1.0681755156  1.0034798763
##  [591,]  0.9380056456  0.693262018  6.129571e-01  0.9577113655  1.2734490110
##  [592,]  1.9335827306  3.961948692  4.805593e-01  0.2605392182  1.2893489240
##  [593,]  1.4985227768  0.452609211  2.218672e-01  0.2880302257 -0.0444072588
##  [594,]  0.1817911080  0.361277127  6.053233e-01 -0.2670161876  0.3514499877
##  [595,]  0.8223674313  3.025113129  4.317650e+00  0.7888815544  0.3923860291
##  [596,]  2.0755237610  2.217903211  1.430388e-01  0.3790790125  0.4281127983
##  [597,]  0.1949173356  0.925557960  2.500622e+00  0.5025394413  0.2116965614
##  [598,]  1.0477513582 -0.014197322  6.547664e-01  0.7247652204  3.0023517988
##  [599,]  6.5756085221  0.736911276  1.737301e+00  2.8003181352  1.1409602764
##  [600,]  1.3361899357  0.018876440  2.211694e+00  0.1470801179 -0.0993684775
##  [601,]  0.5521897213  0.426699907  1.075645e+00  1.2691664382  4.5805772580
##  [602,] -0.1803385240  0.617236103  1.103897e+00  0.1064958984  3.1364410528
##  [603,]  2.7484116902  3.064650717  2.588589e-01  0.0812938277  0.9230971740
##  [604,]  2.6113480545  1.753238431  2.097370e+00  0.2728909644  2.7107949689
##  [605,]  0.7914405410 -0.851148640  2.206574e+00  0.4225574077  0.6188576564
##  [606,]  2.4518901539  0.494187461  1.048663e+00  0.4631983656 -0.3141519259
##  [607,]  0.5283426925  1.244473400  5.020827e+00  0.3400537295  1.8100521687
##  [608,]  0.8836925270  2.194396016  5.014609e-01  1.1060132609  0.8054108792
##  [609,]  0.0786514624  0.563088788 -8.088954e-02  0.6892317017  1.7245503840
##  [610,]  0.7303374083  0.321149398  3.064456e-01  0.5338752739  0.6604469980
##  [611,] -0.1266829108  0.048454923  7.130547e-01  0.0672718931  0.5715107029
##  [612,]  0.9795111676  3.252732207  2.244101e+00  0.7302787195  2.7804912430
##  [613,]  0.2836250138  1.615359963  1.196914e+00 -0.0366099341  0.5656999793
##  [614,]  0.3211792279  0.591741005  1.377122e+00  0.1216806326  0.6141909971
##  [615,]  2.0723017987  0.452928837  4.542330e-01  0.0317172278  0.5108963960
##  [616,]  0.9650584101  1.271661768  7.224865e-01  0.3824913564  0.3369301991
##  [617,]  0.2119132871  0.797918764  8.214919e-01  0.2016490346  1.3649083178
##  [618,]  0.9738681009  0.843713444  3.272805e-01  1.5901811129  0.7322594979
##  [619,]  0.0656665827  5.826313806  3.642518e-01  0.0745208590  1.1318465833
##  [620,]  0.3767127072  0.696376213 -1.148830e-01  0.5224184654  0.3006037438
##  [621,] -0.2080171227  0.341779677  4.840447e-01  0.3320902923  1.2474792729
##  [622,]  3.0232481920  0.654073020  4.770510e-01  0.3427906351  0.1024302901
##  [623,]  1.5160852952  0.446616689  1.616758e-01  1.1353427862  0.6833775654
##  [624,] -0.1693207855  0.277590075  1.288912e+00  1.2784365397  3.8741834010
##  [625,] -0.1223129649  0.240456629  8.433654e-01  0.8390127166  1.2469825023
##  [626,]  0.3033092412  1.390186596  8.608326e-01  0.3705490367  1.2166582359
##  [627,]  0.3099539066  0.293626808  4.112915e-01  1.3698738312  0.1139278997
##  [628,]  0.5694280476  0.785506102  8.828401e-01  2.1444570569  3.6659070767
##  [629,]  3.5148344505  0.615238275  1.065443e+00 -0.1315251947 -0.0018879042
##  [630,] -0.0807041211  0.076331720  3.231489e-01  2.8198962415  0.1571959081
##  [631,]  0.7421969096  1.908468492  2.896090e-01  1.4281092735  0.4279360973
##  [632,]  0.1472731704  0.862631202  3.077910e-02  0.2451151973  0.3757233195
##  [633,]  1.1879396948 -0.022193225  5.257435e-01  2.5061969967  0.0119201896
##  [634,]  1.9375271895  0.244381830  5.618935e-01  1.1333777918  0.4124310617
##  [635,]  0.2461527108  0.669531712  9.075883e-02  3.8143401737  4.9934150383
##  [636,]  0.3164827756  2.001431646  8.149385e-01  4.5472164261 -0.1001116819
##  [637,]  0.0698877591  2.177154996  1.232937e+00  0.2145965729  2.4795721821
##  [638,]  1.5582781543  0.068261572  1.418490e+00  3.4289377658  1.1357988420
##  [639,]  0.2696137748  0.429814391  5.357804e-01  0.5862344247  1.7555273953
##  [640,]  0.3238010475  0.880981385  1.537849e+00 -0.0438304659  0.4477812274
##  [641,]  1.1482669581  0.795256543  4.102018e+00  2.3361171690  0.6265328122
##  [642,]  0.2669708277  0.529916057  6.615550e-01  2.6415239336  0.8833301027
##  [643,]  1.5801111484 -0.449923377  4.922790e-01  1.5330791921  0.3758120441
##  [644,]  0.6578960734  2.386864190  9.550618e-01  1.2641927681  1.2169183772
##  [645,]  0.3122271386  1.211930423  5.698900e-01  0.4708644536  0.4674969646
##  [646,]  4.6510949790  0.349796094  3.956467e-01  3.0319636380  1.5646766085
##  [647,]  0.3026496877  0.644915388  9.073386e-02  0.6775186569  2.5438757591
##  [648,]  1.4453220495  0.441425127  1.434246e-01  0.2813934087  0.4209399448
##  [649,]  2.0898164423  0.946553861  4.750087e-01  1.4461077553  0.5559104340
##  [650,]  0.0945049875 -0.051662329  1.422650e+00  0.3733153809 -0.2380739126
##  [651,] -0.2315583682  0.379568945  4.287220e-01  0.7877528782  1.3986232790
##  [652,]  0.1123548256  0.256250446  6.331366e-02 -0.1508431575  0.6298605148
##  [653,]  0.2197376604  0.274187289  9.050252e-01  0.7497414043  0.1442345963
##  [654,]  0.1949495021  0.168366696  5.357660e-01  1.7397348770  0.2050227408
##  [655,]  0.5639746177  2.646274844  7.241420e-01  0.6361842032  0.4573661679
##  [656,]  4.9894599990  0.141403699  2.728456e-01  2.6444775933  0.2092655675
##  [657,]  1.1248262687  0.312217342  4.078375e-01  0.5028244044  0.0425120300
##  [658,]  0.8063642288  0.400151036  8.467523e-01  0.2769979685  0.6224838825
##  [659,]  0.0868929817  0.024356074  8.331473e-01 -0.0549563435  2.6970501340
##  [660,]  1.1551372909  0.111460935  1.701826e+00  0.3526547941  0.8091404543
##  [661,]  0.8035113843  2.567304869  3.294710e+00  2.8151543531  0.3175852303
##  [662,]  3.1459483472  1.430103228  3.347077e+00  1.1147905201  0.3063296098
##  [663,] -0.0315869521  0.740562338  2.204910e-01  0.8841618755  2.5388277009
##  [664,]  0.3099381123 -0.191361611  1.245901e+00  1.4673605449 -0.0369480586
##  [665,]  1.8539064305  2.725197088  9.843276e-01  0.1794957789  0.5688472685
##  [666,]  1.9749445533 -0.072597269  3.212322e-01  0.3764193337  0.2489112801
##  [667,]  0.0364226109  1.354512095  1.960174e+00  0.2951877469  0.3318122674
##  [668,]  1.1842841537  3.927150213  2.934080e-01 -0.0079463151  0.5596829763
##  [669,] -0.1383537934  1.421514687 -2.703783e-01  2.5854191476  0.8496540772
##  [670,]  0.2658294556  1.233878011  6.088472e-01  0.9964648984 -0.0495307726
##  [671,]  0.5242143872  0.504935997  5.115033e-01  1.9494696115  0.6303304627
##  [672,]  0.0493158390  0.082474257  1.149429e+00  4.0353758419  0.5153419481
##  [673,]  1.0980880292  0.273774175  3.239349e-01  0.5027506645  1.8573781233
##  [674,]  0.9965784241  1.104465956  8.739790e-02  0.2612924959  1.2639490665
##  [675,]  0.4205999266  0.109863630  1.030034e+00  0.7276132395 -0.1264762656
##  [676,] -0.0062424055 -0.023577446  1.251424e+00  0.4420620844  0.5786351338
##  [677,]  0.3732512287  1.559645033  2.270552e+00  2.7285435489  0.8534957594
##  [678,]  0.5554603266  0.494684482 -1.068319e-01 -0.1889322332  1.7862492849
##  [679,] -0.2181630505  0.904977150  1.218973e+00  0.4501230048  0.0092573068
##  [680,]  7.3842376920  0.380309777  4.244098e-01  1.0997083404  3.0835933462
##  [681,]  1.8769276442  1.499208063  1.334103e+00  0.3869269217  0.6344704187
##  [682,]  2.0202364976  1.166274046 -9.013878e-02  1.8485432251  0.1679766359
##  [683,]  2.2328529583  3.349478889  9.827101e-01  0.8246917670  1.3520637343
##  [684,]  0.0524130081  1.009002248  1.410952e+00  0.6231641013  1.0039872497
##  [685,]  0.4745267293  1.169754104  9.962609e-01  2.3561819132  1.2511705748
##  [686,]  4.8193661467  0.484681057  2.201669e-01  0.1886663092  0.2718147805
##  [687,]  2.4893847617  1.375514180  1.857171e+00  3.3510357402  3.2076317401
##  [688,]  0.5440982387  0.827939259  2.675387e+00  0.7547340369  0.6072476638
##  [689,]  0.9422639809  0.662646343  9.440702e-01 -0.0083521787  0.1390018104
##  [690,]  2.3588639944  0.165130386  2.532477e-01  1.4892747977  1.0448231596
##  [691,]  0.0320332219  1.015597894  2.403641e-01  2.3769132981  0.3325201499
##  [692,]  1.0008873093  1.488777174  2.761213e+00  0.5699681367  0.9016184855
##  [693,]  0.3996239919  0.679411612  9.293670e-01  0.0420439751  1.8957992726
##  [694,]  1.2368271883  0.381168537  8.611761e-02  1.1846829316  0.4829221446
##  [695,]  0.8437255114  0.167693400 -5.681162e-02 -0.1327449777  0.6703991686
##  [696,]  0.3370227489  0.933535233  3.877256e-01  0.1957486755  0.5179872057
##  [697,]  3.8771664263  3.934041709  1.126895e+00  2.5772494947  0.7084376368
##  [698,]  0.4061617654  0.880067319  3.330120e-01 -0.0995957014  0.6585191535
##  [699,]  0.5794839508 -0.132063961  3.384368e-01  1.4071721517  2.0119031739
##  [700,]  0.4234482341  1.419446675  1.744772e-01 -0.0828314140  0.3818511346
##  [701,]  6.7905562261  1.500232695 -5.908741e-01  1.6019191221  0.8105566082
##  [702,]  1.9880933532  0.578722942  1.196684e+00  0.5688363553  0.3675746400
##  [703,]  1.5606559624  0.574795314 -3.114563e-01  0.6337513851  3.7739285798
##  [704,]  0.5142572762  1.440487723  1.753638e-01  0.6102261070  1.1433834406
##  [705,] -0.3296007401  2.385072091  2.714653e-01  1.1363507610  0.8729160918
##  [706,]  1.5007500915  0.161517694  1.273808e+00  0.0915366349 -0.0392132654
##  [707,]  0.6077813057  0.465650515  1.251514e+00  0.8394710255 -0.0693866047
##  [708,]  1.6066760160  1.262100442  4.107195e+00  4.1680278896  1.2516736509
##  [709,]  0.9822841697  2.088407681  1.201076e+00  0.1791085737  0.2493967171
##  [710,]  0.8967187431 -0.053650930  1.161577e+00  0.5207366830  2.2777853405
##  [711,]  1.8183333557  0.251126967  1.130008e-01  0.8789662049  1.7631006041
##  [712,]  3.4715379940  2.454765132  2.245935e-01  1.9487088716  3.0082584407
##  [713,] -0.2184092960  0.251365261  6.432796e-01  0.7637530347 -0.1382430688
##  [714,]  4.5518181215  3.214768197  3.089892e-01  0.2214139190  0.3227292054
##  [715,]  1.3604959308  0.868143827 -4.383924e-02  0.7706091305  0.1568678607
##  [716,]  0.9951881815  0.538049410 -3.874982e-02  0.4501685249  0.9132659691
##  [717,]  0.4881674388  0.560023251  1.068633e+00  0.4769688938 -0.1773882838
##  [718,]  0.4612109944  0.061511152  9.601232e-01 -0.0357571341  0.5349325919
##  [719,]  2.1298536647  0.408388008  1.298528e+00  0.3470939361  0.6846525796
##  [720,]  0.3081857105  0.130163359  8.022831e-01  0.2392396533  0.4309012147
##  [721,]  0.0442449006  0.961133243  9.119500e-02  1.0951732537 -0.1143841926
##  [722,]  0.8623450306  0.535393318 -2.384452e-01  0.4267150977  0.6672021366
##  [723,]  0.7196675157  1.820860607  2.332848e+00  0.3780937797  1.0292716126
##  [724,]  2.1772762512  1.166953234  1.154389e+00  1.3057139057  0.5954818763
##  [725,]  1.5955794687  0.774310152  5.589462e+00  1.2982923891  0.2400801927
##  [726,]  2.0828840477  0.342009366  1.531083e-01  0.6428882133  0.3476486965
##  [727,]  1.7269921151  0.118481212  4.244007e-01 -0.0434339613  2.8450498795
##  [728,]  0.5309984925  3.537230879  4.613444e-01  0.9450950592  0.6693861909
##  [729,]  0.2324258312  0.608779723  6.209616e-01  0.0479086983  2.6645168067
##  [730,]  0.3781837359  1.353337448  7.197105e-01  1.5588295464  0.1292656212
##  [731,]  0.2145428569  5.498603912  3.006271e+00  1.1176919033  4.4657789801
##  [732,]  1.0404005488  0.020609510  7.544958e-01  0.7754802397  0.1237407700
##  [733,]  1.7419182030  2.323256698  5.332600e+00  1.0349423603  0.1871011709
##  [734,]  0.0270423695  1.153292730  1.499745e+00  0.9068721710  1.7431039730
##  [735,]  0.4375843048  5.422781323  3.997163e-01  0.4019452603  0.6278688744
##  [736,]  0.8695576330  0.337266894 -1.726974e-01  0.0218447934  0.3387946604
##  [737,]  0.9659837741  1.466938661  1.211933e-01  2.3469721991  0.6425170314
##  [738,]  0.2185832815  0.718845572  8.158084e-01  0.2609476264  0.2676156718
##  [739,]  2.4564325462  0.104003557  2.219578e+00  0.9519330562  1.6414028296
##  [740,]  1.2608068361  1.489716808  4.041456e-02  0.6204392135  2.0634704423
##  [741,]  3.9440265380 -0.114012109  3.874852e-01  2.4652855824  2.1063486368
##  [742,]  0.0256078080 -0.048196255 -1.144630e-01  0.6926302462  0.9713496557
##  [743,]  3.2143603409  0.257345114  1.854817e-01  0.0206848399  1.5489619987
##  [744,]  0.4600600432  2.123101604  6.919245e-01  0.7369769471  1.4084441386
##  [745,]  0.4034329111  0.123824474  8.175372e-02  0.4026990943  1.9825696908
##  [746,]  1.4777188257  1.567628352  7.689323e-01  0.3012433031  0.2083317506
##  [747,]  1.7962480565  1.361089760 -2.567174e-01 -0.1369790292  0.5993222586
##  [748,]  0.6611879994  2.258890395  1.203685e+00 -0.3546135975  1.2520855883
##  [749,]  1.8760286680  4.503209779  2.217099e-02  2.3304150066  0.9725382986
##  [750,]  2.1999411478  1.236922798  2.719126e-01  2.3832191530  5.7621622065
##  [751,]  5.7516168355  0.781538530  1.303712e+00  0.3490125443  2.0634113689
##  [752,]  7.3946586974  1.184512106  1.627298e+00  0.1482443741  1.4375150656
##  [753,] -0.0750098824  2.489255847  6.359416e-01  0.3566972572  0.8248949574
##  [754,] -0.2959975944  0.997116883  1.402154e+00  0.2012945718  0.5550950665
##  [755,]  2.0962151975  1.737139010  2.143127e-01  3.4135990166  0.0571824107
##  [756,]  1.5036133693  2.665640600  4.935654e-02  2.3605077439  0.2477467369
##  [757,]  6.0438449411  0.767153876  5.315742e-02  1.6903341736  0.5514014808
##  [758,]  0.3134513604 -0.055246325  1.853787e+00  2.1013151529  1.6979017283
##  [759,]  1.1243732913  0.175843539  5.235026e-01  0.6725642656  0.2037299350
##  [760,]  1.4891080335 -0.224155423  2.237782e+00  0.0785505386  0.6107074970
##  [761,]  0.5395263692  1.245129262  1.573634e+00  0.0160065340  0.8262293854
##  [762,]  0.0393669894  0.021976567  7.022551e-01  2.4332699409  0.7685732535
##  [763,] -0.2483020793  0.490087449  1.289765e+00  2.9613328615  2.2074813791
##  [764,]  1.5460556991  0.077457864  7.692190e-02 -0.1565764391  0.0637769372
##  [765,]  1.7281292898  1.377181453  2.861575e+00  0.1209639474  0.3342713214
##  [766,]  0.5123065216  1.550367414  1.953579e+00  2.0424212478  1.0820098642
##  [767,]  1.0958581869  6.503705022  9.153764e-01  0.4156455046 -0.0823728284
##  [768,]  0.1917215856  1.275905155  2.869049e+00  2.2540402687  0.5029177965
##  [769,]  0.5978157097  2.160265809 -1.422626e-01  0.4127047158  0.0746618426
##  [770,]  0.8840217722  1.065847852  2.180852e+00  0.6373841447  4.2592532456
##  [771,] -0.5149934893  1.086389906  2.621041e-01 -0.0180998909  0.5082829294
##  [772,]  1.3293557037  2.278200381  5.632012e-01  0.9241232217  1.2453936347
##  [773,]  1.0893014381 -0.157293116  1.128013e+00  1.8662987907  1.5939257834
##  [774,]  0.4315369232  0.748262779  4.018974e-01  0.9345380761  2.3414243195
##  [775,]  0.8739085249  1.332990896 -7.584166e-02  2.6133676270  0.5404548009
##  [776,]  2.3780113011  2.543960858  4.918461e+00 -0.0276526838 -0.2375890614
##  [777,] -0.1182604960  0.177460630  9.041606e-01  0.3261234030  4.2694656871
##  [778,]  0.2633737402  1.024197215  6.305448e-01  1.9998079605  0.4122005381
##  [779,]  0.7516554727  0.103642202  1.112532e+00  1.3450552334  0.2720778409
##  [780,]  0.1360403324  0.475588776  8.349757e-01  0.9270331815  4.5106340048
##  [781,]  0.7033588448 -0.009941351  7.836319e-02  1.4488003998  0.0405258198
##  [782,]  3.9800170615  1.651980869  3.281175e+00  2.2778690696  0.4736737153
##  [783,]  1.5524046916  0.282105453  2.951766e+00  1.0263895280 -0.0336059063
##  [784,]  0.4653154879  0.304038969  1.008249e+00  0.7441964746  0.1442600846
##  [785,]  0.2491716814 -0.039288260  1.093209e-01  0.1895570057  4.7746066491
##  [786,]  1.7974840979  0.530623984  8.861136e-01  3.2239124371  1.3110943838
##  [787,] -0.0262464255 -0.200491312  1.322347e+00  3.4269979859  1.3632804390
##  [788,]  0.9023033339  3.385862130  1.400402e+00  0.0492431174  1.1157490408
##  [789,] -0.0619067002  1.669458033  1.886161e+00  0.8933842840  1.3585892770
##  [790,] -0.0208839294  0.497231683  1.021524e+00  1.7465598001  0.2515498190
##  [791,] -0.1527843010  0.106200397  5.127281e-01 -0.2128066943  1.3048817029
##  [792,]  0.7454038299  0.228026871  1.076935e+00  1.0455800203  2.0862216656
##  [793,]  0.3165580711  0.868501717  1.015378e+00  0.5399965685  0.5623683045
##  [794,] -0.1488649489  1.219206642  2.187337e+00  0.0748805417  0.7248106143
##  [795,]  0.3419212756  0.708148719  4.407002e-01  0.3282627754  0.1273439619
##  [796,] -0.2251809256  1.194087902  1.708203e-01  0.0865650271  0.8241656738
##  [797,] -0.0827026993  3.490707174  1.110828e+00  0.7362437133  0.5778219791
##  [798,]  0.0535285445  0.170854419  1.750021e+00  1.0615225890  0.5664144308
##  [799,]  1.6090868716  0.703243595  3.761153e-01  1.2175225496  1.7703711732
##  [800,] -0.1472542249  0.206563199  3.599644e-01  4.4908320342  0.2325706483
##  [801,] -0.0339372691  0.838168867  1.552474e+00  0.5592788294  3.0941602878
##  [802,]  2.4655504979  1.075871062  2.894049e+00  0.3048863230  0.2066671663
##  [803,]  0.1638948491  0.049706298  1.529066e+00  0.3705782892  0.8721576165
##  [804,]  0.1641026759  1.959142336  3.202119e-01  0.4075282816 -0.1586364806
##  [805,] -0.2583265582  0.606513668  9.449067e-01  0.6108337015  0.0886485530
##  [806,] -0.1489005073  0.292319378  1.210655e+00  0.3918443743  1.8419572472
##  [807,]  0.5037549986  1.195349010  2.629999e+00  1.4166590663  1.4599899101
##  [808,] -0.1094207325  2.843189040  1.391976e+00  1.4490507561  1.5192475314
##  [809,]  0.6660933566  2.109834916 -1.570324e-01  0.5425842575 -0.1915178800
##  [810,]  0.9291342244  0.999608933  9.324936e-01  0.6930087673  0.0990060442
##  [811,]  1.6844106387  0.326866343  4.971207e-01  1.6554683535  1.3614004590
##  [812,]  0.2242371091 -0.187660416  1.843398e-02  3.0550322506  1.3738895818
##  [813,]  0.6639471228  1.206681158  1.827375e+00  1.2987221762  2.4006350319
##  [814,]  0.1251979152  0.565651718 -8.336723e-02  1.4409942262  2.3061614848
##  [815,]  0.6196903239  0.283241629  2.537114e+00  0.8527122789  1.3277311974
##  [816,]  1.9111685645  0.598949871  1.025863e+00  0.8923823397  0.4597034524
##  [817,]  0.4771870209  0.392071352  6.009725e-01 -0.2105936225  0.1473178146
##  [818,]  1.1992197756  1.648888435  1.291501e+00 -0.1898362925  2.3072544287
##  [819,]  0.0335085948  1.646221291  7.010977e-01 -0.0889597126  1.0198939222
##  [820,]  0.0496444177 -0.035285656  7.775296e-01  0.2119008087  1.9547092360
##  [821,]  1.9717746083  1.331924592  1.023362e+00 -0.1246776813  1.9047113593
##  [822,] -0.4760603460  2.808742628  5.046314e+00  0.0566304277  0.1406674464
##  [823,]  1.5090708158  0.377154529  1.106343e+00  0.5417166892  0.4087407707
##  [824,]  0.2243694539  0.128784362  1.473088e+00  1.8223779363  0.6866048337
##  [825,]  0.4524131301  7.536258409 -2.022883e-01  0.7791905444  1.3094833759
##  [826,]  0.4943096992  1.656286950  1.314553e+00  1.6858923860  0.3425650325
##  [827,]  1.1532957418  0.482741133  4.219855e-01  0.3556483539 -0.0260736722
##  [828,]  1.5853441588  1.257511109  5.717487e-01  1.0862881784  0.2207953246
##  [829,]  0.0270711571  0.435158693  4.178400e+00  0.0483528166  1.5898604817
##  [830,]  1.2782449882  0.072185971 -1.929751e-01  2.0784183064  0.1586121049
##  [831,]  0.6940079121  0.173713117  1.192704e+00  3.3956811583  0.3238939695
##  [832,]  2.7965983708  0.638418757  4.417502e-01  3.5308261050  1.0243109000
##  [833,]  0.3886862701  0.961621742  6.707471e-01  0.9473621951  0.6751906285
##  [834,]  1.3791463711  1.373993229 -1.810638e-01  3.2864264668 -0.1779023760
##  [835,]  1.3235595296  1.060359494  2.119342e+00  0.8619899338  0.9457199328
##  [836,]  0.9412765553 -0.260345717  8.752948e-01  0.1256115871  1.9232522678
##  [837,]  1.0093306763  0.543009193  4.704374e-03 -0.1914116014  0.1270322057
##  [838,]  0.3591716595  0.358516111  3.524686e-01  0.2386030654  1.0966549863
##  [839,]  1.0983515702  0.858221329  3.296026e+00  0.0906215361  0.7253029703
##  [840,]  0.7936722704  0.167921029 -5.402520e-02  3.9980033565  0.6658786302
##  [841,]  0.7988601383  1.755486612 -1.490824e-01  0.9520184947  0.1799451489
##  [842,]  0.0503220786  0.866535614  1.917580e+00  1.0201640198  0.3012180357
##  [843,]  1.0523974634  0.655078792  1.419641e-01  1.1896746734 -0.1524113767
##  [844,]  1.3576949607  1.394263997  7.232841e-01  4.1284799478  4.0718873805
##  [845,]  2.8849234577  2.167700161 -5.614885e-02  0.4129319665  2.5379111666
##  [846,]  0.6967236150  3.773082373  8.066238e-02  0.5129701030  1.0367501976
##  [847,] -0.1729524920  0.334886818  1.099871e+00  0.3874262462  0.3707741070
##  [848,]  2.1735349224  0.497140987  5.313483e-01  0.5787750340  2.4363499908
##  [849,]  2.8569127351  2.361136505  7.937957e-01  0.0393453855  0.1457752027
##  [850,] -0.2813435551  1.660104079  3.612266e-03  0.8808754668  2.0866721382
##  [851,]  0.7994737881  0.444262810  4.341465e-01  3.1008841924  0.2426866960
##  [852,]  0.1796608077  0.458511940 -2.265067e-02  1.3310152723  3.5235801219
##  [853,]  0.8865466751  0.300813732  3.869064e-01  0.7475534477 -0.3002543485
##  [854,]  2.0764715877  0.141421277  5.411097e-02  0.2198660613  1.9345385655
##  [855,]  3.0526788929 -0.197014481  2.264037e+00  1.6322320863  1.9686105907
##  [856,]  1.6771295715  0.643329383  4.095912e-01  1.1004026265  0.0291214929
##  [857,] -0.0763819275  0.443454494  2.524862e-01  0.8543295821  0.4279884054
##  [858,]  1.0312303503  0.476129900  1.822466e+00  0.8520577191  1.4057825657
##  [859,]  1.1642921189  2.716322619  1.117965e+00  1.6938418305  0.7646108397
##  [860,] -0.0352443054  7.116186436  1.925496e+00 -0.1774670046  1.3837258032
##  [861,]  1.3971798876  0.305824529  1.146241e+00  0.4941888880  0.4575597195
##  [862,]  1.1329543153  0.211017688  2.527727e+00  0.4757581991  3.0222484206
##  [863,]  0.3308073278  0.083409946  3.923267e-01  0.5145492998  2.2556463778
##  [864,]  0.3615995673  6.542241862  7.947186e-01  0.6950261612  2.5054415914
##  [865,]  0.0073474185  0.869958045  9.684161e-01  0.2053622347  0.5319804304
##  [866,]  1.0616863745  0.514057537  7.498886e-01  0.9807011869  1.0984233243
##  [867,]  0.1010006801  1.455146670  1.122933e+00 -0.0793331859  0.1324376462
##  [868,]  3.8129945698  0.538080897  7.842982e-01  2.0740304793  1.1569539692
##  [869,]  0.2243194423  0.846017093  2.643721e-01  0.0844665217  0.7176017116
##  [870,]  2.3773832819  1.271889519  6.997007e-01  0.3646226379  0.8512654372
##  [871,]  1.9962278643 -0.087275966  1.974334e-01  0.5199761374  0.4795919568
##  [872,]  0.2453311818  0.979697464  9.399251e-01  2.2690589433  0.1265644507
##  [873,]  1.0331912121  0.166299659  6.767001e-01  3.3657351072 -0.1876732352
##  [874,]  0.3077421543  0.255388182  1.821048e-01  0.2126963066  1.4593981083
##  [875,]  1.7733833737 -0.059674736  1.293780e+00  0.9369745370 -0.3804122365
##  [876,]  0.4275032460  0.439542760  1.816041e-01  1.4981954316  0.8624895722
##  [877,]  2.2161436273 -0.017938833  9.208492e-01  0.9614514645 -0.0302622886
##  [878,]  1.9341594505  0.244292675 -1.374327e-01  1.1569511854  0.8527016691
##  [879,]  0.2000480880  1.410385573 -1.071755e-01  1.1786841059  0.3859058958
##  [880,]  1.0920972795  0.786509221  8.438539e+00  1.4603672720 -0.1039914243
##  [881,]  1.5066925375  0.311347179  2.114293e+00  0.5750921226  0.1498532432
##  [882,]  0.3252647224  0.757760736  6.273208e-02  0.9544991980  0.2886648299
##  [883,]  0.7302227087  1.106959434  5.750672e-01  3.6766619740 -0.0512853377
##  [884,]  3.2096282580  0.076864730  1.291579e+00  1.1201382408  2.0345189715
##  [885,]  0.5054938808  0.333466038  7.812225e+00  0.6789900294  2.8396039644
##  [886,]  0.1441266946  1.437272490 -1.615670e-01  0.3390021479  2.7079400596
##  [887,]  0.0031473098 -0.205267961  1.431411e+00  0.8255894023 -0.0341747177
##  [888,]  0.5712809055  0.039263472  6.420094e-01  0.0173580572  0.8969654602
##  [889,]  1.2223167180 -0.362941676  2.210229e-01  0.0649746222  1.6458598250
##  [890,]  3.3383907569  0.863189111  2.497442e-01 -0.0800072238  5.7210636463
##  [891,]  1.1135372500  0.085348708 -1.251066e-02  1.9159195809  1.7380460355
##  [892,]  0.5010137345  0.556480456  1.560175e+00 -0.2345528434  0.1169865308
##  [893,]  0.6075874591  1.457554668  1.528334e+00  0.3863511110  0.8901862380
##  [894,]  1.0853306172  1.371499984  7.648758e-01 -0.0637235513  0.1327613567
##  [895,]  0.0098921361  0.356436824  3.163353e-01  1.5655217063 -0.2325822879
##  [896,]  0.8874588410  3.095341372  5.269681e-01 -0.1331212263  0.5237143486
##  [897,]  0.9295798766 -0.246056287  2.100730e+00  2.1771581483  1.2380889713
##  [898,]  0.3031690256  9.319403588  4.326620e+00  1.1446779739  0.8392307490
##  [899,]  1.2865960911  0.050744538  3.332531e-01  0.1752857757  2.0955921427
##  [900,]  0.6430278566  0.378672396  9.140850e-02  0.5630544601  0.3117430637
##  [901,]  4.3729108726  0.081818097  4.143416e-01  0.2040962196  2.4230073214
##  [902,]  0.0864407229  0.106940610  6.360843e-01  0.6409489120  0.5638411247
##  [903,]  0.2952174863  0.399444155  1.541372e+00  2.3926241319  0.0317853197
##  [904,]  0.5994001759  0.624538022  3.486266e-02  2.4885116357  0.7121435690
##  [905,] -0.0056538006 -0.192055619 -2.102022e-01  0.5677587674  0.3615287690
##  [906,]  0.5752436147  0.108982189  2.521474e+00  0.7971448408  3.0863365120
##  [907,]  0.2167961214  0.242440409  3.976376e+00  0.6463680313  0.8677091237
##  [908,]  0.3053690670  0.594727416  4.122376e-01  0.6016001895  0.2763735224
##  [909,]  1.1290236759  0.223990640  1.422157e+00 -0.3551714737  0.0429970476
##  [910,]  1.6817022846  1.709078824  1.970924e-01  0.1880325928  0.9133363740
##  [911,]  0.4712778155  0.988636332  3.864188e+00  1.2199639465  0.7264191288
##  [912,]  1.8581050182  0.120484847  3.942363e-01  1.1626051210  2.9630050876
##  [913,]  0.2145923133  0.859394839  1.982153e-01  0.9916162682  0.3031341068
##  [914,]  0.6171789760  0.137239538  3.585715e-01  1.2624791087 -0.0353819825
##  [915,] -0.0264747373  0.114165080  9.201949e-01 -0.0330592431  0.2669859315
##  [916,] -0.4635092641  2.241988293  2.485760e+00  0.4012448708 -0.0834811724
##  [917,]  5.0923093827  1.869565907  8.031053e-01  4.5244204063  0.6920689861
##  [918,]  1.4554254979  0.738150562  1.427177e+00 -0.1659761265  0.8279491993
##  [919,]  0.3215176941  1.123209775  1.917987e-01  0.5875041036  0.2408042548
##  [920,]  0.4769425131  0.111424573  2.099543e+00  1.9193668910  2.8138103639
##  [921,]  0.4389606019  1.011276460  2.825971e-01  0.6740073829  1.0026986313
##  [922,]  0.9811584878  1.750291246 -2.473834e-01  0.5566374880  0.6434623600
##  [923,] -0.1613245028  1.544734852  1.725303e-01  1.6976254673  1.3538959472
##  [924,]  3.0729684043 -0.131413892  4.600969e-01  2.1625041735  1.6524165755
##  [925,]  0.7778219675  1.921502680 -3.935012e-02  2.6766548364  2.3991327279
##  [926,]  4.3839066439  1.716096441  8.296705e+00  1.1924473765  1.3523201483
##  [927,]  1.4913332898 -0.032195422  4.064929e-01  0.9876456395  0.7510315699
##  [928,]  5.4883154499  0.003872453  9.502789e-01  1.7189334973  2.5093205040
##  [929,]  0.0757181345  1.270728206  1.739146e-01  0.5294328481  0.2409046875
##  [930,]  1.0147852220  0.242390455  1.602823e+00  1.8566255443  4.2395183728
##  [931,]  0.3292964522  0.552844266  1.715761e+00  0.0468079386  0.5839883025
##  [932,]  3.9504992060  1.079231002  1.665948e-01  1.2164701017  0.4486018126
##  [933,]  0.1599380575  0.786334748  1.489272e-02  2.7896788268  1.6651235532
##  [934,]  0.5362160716  0.199918853  1.254678e+00  2.4516365002  0.6062471070
##  [935,]  1.2684357405  1.432940660  6.630107e-01  0.9391371030  1.2732662684
##  [936,]  1.5454125994  1.486117884  1.236869e+00  0.2047676163  0.7127716434
##  [937,]  0.9598398496  1.356893104  1.006596e+00  1.1739328767  0.0828901681
##  [938,]  0.9198012774  0.282176721  5.954129e-01  2.6877127973  0.6102767741
##  [939,]  0.6760136848  2.320327943  1.000990e+00  0.6487363324  1.9714392224
##  [940,]  0.1354712512 -0.099485945  2.112291e+00  1.2803624132  0.3116611331
##  [941,]  2.4572002534  3.108188180 -1.303666e-01  6.0327231303  1.9676010911
##  [942,] -0.0182798411  1.025959311  7.310634e-02  0.6450611962  0.1605493786
##  [943,]  1.3180174243  0.855125840  3.799932e-01 -0.0985350039  0.7635407293
##  [944,]  0.6656307371  2.473359435  1.469578e+00  2.6535935075  1.6717255310
##  [945,]  0.3087404871  0.892401075  4.030001e-01 -0.0301822563  5.5378794532
##  [946,]  0.6787053961  1.131677104  4.253470e-01  0.2110807592  0.0304808590
##  [947,]  0.8188109668  1.034620227  8.421023e-01  2.5887179183  1.2995273473
##  [948,]  0.4518402257  0.761149052  3.844011e+00  0.8997308569 -0.2925953055
##  [949,]  0.6945772327  6.092917447 -7.400334e-02  1.4418987168  0.0341430507
##  [950,]  2.7560174628  0.001241652  1.605775e-01  1.1950213553  2.7380681136
##  [951,]  0.4848823285 -0.077564918  5.548978e-01  0.8038726144  0.8618786333
##  [952,]  4.6780589118 -0.225909231  7.430485e-01  0.5896416501  1.3932658658
##  [953,]  0.2519282198  2.532964668  8.679762e-02  0.8704877911  1.3522048524
##  [954,]  1.4821928720  0.671220892  1.184411e+00  3.2635506760  0.0563442789
##  [955,]  1.9969746146  0.720249257  7.888495e-01  7.0084554055  0.5111886336
##  [956,]  1.0418807961  2.022627466 -3.499683e-01  0.9561214107  1.2161441283
##  [957,]  1.8272147104  0.671168780 -9.947271e-02  0.9349137114  0.3752673463
##  [958,]  2.0762023910 -0.234349134  2.440859e+00  0.3446592353  2.2581050522
##  [959,]  0.3467349486  0.978984975  1.096785e+00  1.0711008084  4.2985872771
##  [960,]  2.5249154763  1.071223786  2.906373e-02 -0.3141244533  0.4114697431
##  [961,]  1.1254840325  0.807452464  4.867697e-01  0.4124197337  0.2329695946
##  [962,]  0.7093635863  0.099281850  3.064182e+00  1.2003510529  2.5387997643
##  [963,]  0.7609193170 -0.076748059  8.582511e-01  1.5446038065  3.3075105350
##  [964,]  2.8673473055  0.352470818  1.805082e-01  1.4546904217  0.8231884197
##  [965,]  0.0686733841 -0.039330387  2.906751e-01  0.5423467893  0.8392881048
##  [966,]  0.3936683316  1.256521080  3.738371e-01  0.4616967579  0.9919036485
##  [967,]  1.1785523047  0.233824128  2.184477e-01  0.2002499623  0.7244523151
##  [968,]  0.8023350374  1.948389861  4.777493e-01  0.7824134644  2.5762358277
##  [969,]  0.8119715313  1.143851175  7.687723e-02  2.7042873267  1.3031404606
##  [970,]  0.0083779673  3.120567981 -1.637643e-03  0.1602961503  0.4927576305
##  [971,]  0.1890483972 -0.204807680  1.129172e+00 -0.0349470976  0.4511556618
##  [972,]  0.0108235412  0.439889116  7.462469e-01  0.3474831351  0.1612432195
##  [973,] -0.0739739307  0.496157321  4.437046e-01  0.5131950568  1.7326936942
##  [974,]  4.4438074647  0.933877435  1.752792e+00  0.1176321705  0.7677415678
##  [975,]  0.7900632031  0.154469077  4.843650e-01  1.8487522549  2.1317222130
##  [976,]  2.5511069614  1.734073327  8.204547e-01  0.0245346307  0.5598540146
##  [977,]  0.0870354765  1.428754308  7.172231e-01  0.2761210913  0.2593808205
##  [978,]  1.5384876680  0.878568122  4.086792e-03  1.4109998077 -0.1121479412
##  [979,]  0.9884853457  0.612530055  3.249161e-01  0.0718034644  0.7094458565
##  [980,]  0.0692871822  0.693610725  1.108412e+00  1.4643840474  0.4218643841
##  [981,] -0.0211462835  0.551666853 -4.318177e-02  1.9075825125  2.9073892486
##  [982,]  0.3325721731  2.325215472  7.310116e-02  1.6725694013  0.1679398089
##  [983,]  0.4823645101  0.672950810  2.429767e-01 -0.0961071556  1.6988049792
##  [984,]  0.1745091245  4.195301084  3.229286e-01 -0.2313426459  1.3969705074
##  [985,]  0.3737866951  2.065461430  1.934522e+00 -0.2382319568  7.1953623861
##  [986,] -0.1887830310  1.331207359  4.104394e+00  0.3845732015  0.4063162944
##  [987,]  0.5643773482  1.285013634  9.994566e-01  1.3868537778  0.8447855532
##  [988,]  0.2273873799  0.314532592 -5.110414e-02  1.0639951138  0.5672218683
##  [989,]  1.7542822165 10.691611945 -4.191890e-01  0.3259904128  0.0733473336
##  [990,]  3.6795149555  0.181818239  3.715355e+00  0.6260867762  0.0123076025
##  [991,]  0.9753595721  0.859588863  8.662844e-02  0.6540826538  0.6150825845
##  [992,]  2.0566939617  1.509644421  2.646109e-01  0.3861237350  0.5800721156
##  [993,] -0.1468224683  0.047666186  2.897290e+00  1.2526947252 -0.1061010420
##  [994,]  0.0975353542  0.216087246  1.877705e+00  0.9029421700  3.2020031940
##  [995,]  2.0584721967  6.154361570  3.082782e+00  0.3416637634  0.6394911721
##  [996,] -0.1507517322  1.044690982  5.922229e-01  2.9785661060  0.5255172390
##  [997,]  0.5312509187  5.723316788  5.209112e-01  0.7878521962  0.1924484438
##  [998,]  2.7434096121  2.823325826  1.250381e+00  1.2884250860  0.1783529860
##  [999,]  0.9431289372  3.177416297  1.769789e+00 -0.0921535567  0.5407750493
##                 [,11]        [,12]
##    [1,]  2.1809107221  7.373981205
##    [2,]  2.5348151525  1.974098921
##    [3,]  1.9382047905  0.001894576
##    [4,]  0.6030566451  1.295277666
##    [5,]  0.2829616231 -0.435217995
##    [6,]  1.3704562945  0.758004260
##    [7,]  1.1264094482  0.512551809
##    [8,]  0.3886855423  1.746030585
##    [9,]  0.1942796773  0.818986388
##   [10,]  0.9434897606  0.067996109
##   [11,]  2.8722577753  1.274635961
##   [12,]  1.4251206190  0.212437008
##   [13,]  0.2023569654  1.000807233
##   [14,]  1.2300711817  0.701097419
##   [15,]  0.5958562541 -0.242499924
##   [16,]  0.8972727010  4.907472392
##   [17,]  2.9771431817  0.257404002
##   [18,]  0.6900633531  0.796872238
##   [19,]  0.6259923917  0.815581047
##   [20,]  0.3539019900  2.030653156
##   [21,]  1.1572432871  1.068114267
##   [22,]  0.6294804230  1.868075092
##   [23,]  0.3699432091  1.210686922
##   [24,]  2.3659402752  0.947356614
##   [25,]  0.0852735433 -0.353963229
##   [26,]  0.6520302347  0.069917766
##   [27,] -0.1172042113  0.627904127
##   [28,]  0.6519144939  1.578001225
##   [29,]  6.1687618249  5.349809281
##   [30,]  0.5226517237 -0.156490180
##   [31,] -0.1823405966  0.608573987
##   [32,]  0.8417745481 -0.320424787
##   [33,]  2.3329356516  0.366506286
##   [34,]  2.2150155135  2.877951692
##   [35,]  0.5264890415  0.616372755
##   [36,]  0.8239279058  0.806601118
##   [37,]  0.8166929449  1.402512975
##   [38,]  2.1802138318  0.267092136
##   [39,]  1.5800129194  1.786743699
##   [40,]  1.6594260493  0.968426044
##   [41,]  0.4584890265  2.068228464
##   [42,]  0.9479189607 -0.193353445
##   [43,]  0.2611141291  2.080580466
##   [44,]  0.2475045262  0.208808206
##   [45,]  0.3414535097  1.334603292
##   [46,]  0.7879532749  0.654844391
##   [47,]  4.3416569701  0.248213717
##   [48,]  0.0852215199  2.972916945
##   [49,]  0.4358434675  0.724689308
##   [50,]  0.0677614085  3.126883323
##   [51,]  0.9558493082  1.492917578
##   [52,]  0.9027638786 -0.083941828
##   [53,]  1.6544676150  1.996231002
##   [54,]  6.2754555485  0.811975190
##   [55,]  1.4536036411  1.210682991
##   [56,]  0.5270195508 -0.012205005
##   [57,]  0.2935783096  1.174737329
##   [58,] -0.1865028023  2.784606331
##   [59,]  0.3502405686  0.563880243
##   [60,] -0.0104512137  0.599520218
##   [61,]  0.9305478123  0.909801399
##   [62,] -0.1822943798  0.612508112
##   [63,]  0.5398223061  1.191323858
##   [64,]  0.5894510630  1.095271253
##   [65,]  0.0043346746  0.641182439
##   [66,]  1.2111875988  0.855005107
##   [67,]  0.0049792423  0.198933301
##   [68,]  2.7109148307  0.516686566
##   [69,]  2.2721424233  0.259587785
##   [70,]  0.1569489533  0.175211395
##   [71,]  2.7491284098  1.643726960
##   [72,]  1.5415978363  2.627825869
##   [73,]  1.3757000033  0.151991532
##   [74,]  0.4318854811  0.606448993
##   [75,]  1.1822359745  0.635935865
##   [76,]  0.8077804400 -0.274696972
##   [77,]  1.7375388763  2.573498997
##   [78,]  0.5382105284 -0.026866334
##   [79,]  2.2287827467  0.765947324
##   [80,]  2.8811312728  2.409190333
##   [81,]  1.0735636836  0.603887565
##   [82,] -0.2133022041  0.114008250
##   [83,]  0.8176132238  2.977035046
##   [84,]  0.8677255531  0.265641725
##   [85,]  1.2340303240  1.584957608
##   [86,]  0.3272597235  0.243784859
##   [87,]  2.2092381619  0.545808265
##   [88,]  0.7877925161 -0.216590313
##   [89,]  0.4613419539  0.425015211
##   [90,]  1.9025295910  1.082783476
##   [91,]  0.9187098234  0.527394070
##   [92,]  2.2234651634  8.942810783
##   [93,]  0.0198883773  2.024317160
##   [94,]  0.6582333577 -0.010392680
##   [95,]  0.4332699892  1.166326595
##   [96,]  0.1587348257  0.094700513
##   [97,]  0.4865647024  0.546477637
##   [98,]  0.6088866791  1.998154366
##   [99,]  1.5806753461 -0.139906754
##  [100,]  0.9175280558 -0.098001113
##  [101,]  2.2657493157  1.152297236
##  [102,]  0.9374733886  0.416453748
##  [103,]  0.5860659287  1.037717177
##  [104,]  0.7578994633  1.498624708
##  [105,] -0.0445712595  2.747812553
##  [106,]  2.5583778424  2.327119956
##  [107,] -0.4554639090  1.611663699
##  [108,]  1.1422241098  1.601296689
##  [109,]  0.4978186533  0.156539336
##  [110,]  0.5291185918  2.243727048
##  [111,]  0.6755044042  0.767428690
##  [112,]  1.4065393731  0.208423735
##  [113,]  0.5187793525  0.587314018
##  [114,]  0.3554055374  1.411749420
##  [115,]  0.6787848422 -0.018903226
##  [116,]  2.2733626161  0.396739432
##  [117,]  0.8367918824 -0.121862376
##  [118,] -0.0980671447  0.597280278
##  [119,]  0.1078781760  0.067659528
##  [120,]  1.0022449679  0.208803692
##  [121,]  1.6199353049  2.046371045
##  [122,] -0.0724367474  0.486826203
##  [123,]  0.8448331084  1.800344536
##  [124,]  1.9210348729 -0.148308092
##  [125,]  1.1979906881  1.119426549
##  [126,]  3.1606525259  3.170048694
##  [127,]  0.6541586761  0.755791334
##  [128,]  0.5850068069  0.569766821
##  [129,]  1.1334682383  0.167309707
##  [130,]  1.0055546996 -0.279975566
##  [131,]  0.1808699404  2.056085188
##  [132,]  0.4871871238  0.462391260
##  [133,]  0.7729611515 -0.225474889
##  [134,]  2.1979246836  0.370644641
##  [135,]  0.0690678237  1.591866716
##  [136,]  0.5468978140  0.292104759
##  [137,]  0.5748318033  1.423438637
##  [138,]  0.6435995315  0.261392791
##  [139,]  0.2658316069  0.929553520
##  [140,]  2.3807133030  1.064237056
##  [141,]  1.0192453441  1.178104215
##  [142,]  0.5833318813  0.903889031
##  [143,] -0.3128710972  0.427466465
##  [144,]  0.2318435881  0.174544883
##  [145,]  3.2250479336  1.300775302
##  [146,]  1.3591300538 -0.207437946
##  [147,]  2.0886903317  0.930329690
##  [148,]  0.2785002817 -0.232289263
##  [149,]  5.1988765456  3.140041458
##  [150,]  1.4134153214 -0.176909131
##  [151,] -0.0869831360 -0.003689010
##  [152,]  0.1522734109  2.908243602
##  [153,]  0.0985465508  0.403851076
##  [154,]  1.1063255291  1.675228038
##  [155,]  1.7665552601  1.554931693
##  [156,]  1.6501247171  2.534193757
##  [157,] -0.2276668713  1.465180111
##  [158,]  3.8740531102  1.839379177
##  [159,]  1.2690342221  0.984347861
##  [160,]  0.0944083961  0.520403987
##  [161,]  1.9325435359  0.022564085
##  [162,]  0.4829544475  1.411379164
##  [163,]  0.1677180100  0.976921371
##  [164,]  0.8040410395  0.270394555
##  [165,]  0.5378395141  0.651445918
##  [166,]  4.9005699087  1.096388952
##  [167,]  1.0632426090 -0.053704470
##  [168,]  0.4321958418  1.432332501
##  [169,]  2.4895201613  0.980740729
##  [170,]  0.9359765028  2.126262152
##  [171,]  1.0918084013  0.741827976
##  [172,]  0.4422947793  0.618940250
##  [173,]  0.0326211780  0.610660431
##  [174,]  0.6162892400  0.967855040
##  [175,]  0.5698054139  0.290783102
##  [176,]  0.2597668892 -0.050876055
##  [177,]  1.3201146681  0.425125857
##  [178,]  0.4013106496  1.482004956
##  [179,] -0.0656579685  0.249567040
##  [180,]  0.5176676340  1.546846342
##  [181,]  0.3995186705  0.329099445
##  [182,]  3.3462193955  4.635288265
##  [183,]  1.0485401013  1.434354963
##  [184,]  0.1795666496  1.775565679
##  [185,]  4.3781447251  1.212160430
##  [186,]  0.9047462997  0.308703676
##  [187,]  0.9167028293 -0.013729639
##  [188,]  0.4718032795  1.132422491
##  [189,]  1.1630207343  0.825355946
##  [190,]  0.2786997882  2.150932638
##  [191,]  1.7125572190 -0.032386137
##  [192,]  2.2720209163  0.838389454
##  [193,]  0.2043024921  2.190581775
##  [194,]  0.1009078180  0.161405146
##  [195,]  0.8908191690  0.121648915
##  [196,]  0.6003176601 -0.619237509
##  [197,] -0.0878509364  1.113786281
##  [198,]  2.1700839256  1.120031557
##  [199,]  0.7906264558  0.250085441
##  [200,]  3.3287903385  1.240098626
##  [201,]  2.2225789132 -0.103738175
##  [202,]  1.6493965982  0.520595690
##  [203,] -0.1918307699  2.412018583
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##  [205,]  0.9734653848  4.924740009
##  [206,]  1.9602364895  1.457381856
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##  [208,]  3.1897125842  2.549174377
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##  [210,]  0.1218151613  0.381804372
##  [211,]  0.4156627808  0.225394443
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##  [694,]  0.3360296861  2.557839456
##  [695,]  0.4069642406  0.557009593
##  [696,]  0.1212958998  0.313795365
##  [697,]  0.0263668594  2.520195623
##  [698,]  6.8577443144  0.474320526
##  [699,]  1.1617542576  0.459417032
##  [700,] -0.1360462978  0.758310382
##  [701,]  2.5771628099  2.674685132
##  [702,]  0.3211035889 -0.070501530
##  [703,]  3.1257072550 -0.051703914
##  [704,]  0.3407657833  1.279381887
##  [705,]  1.9254144100  0.657836918
##  [706,]  0.7791203772  0.790260895
##  [707,]  0.1683476247  0.670626112
##  [708,] -0.1084818477  0.412257036
##  [709,]  1.9440278293  2.366261236
##  [710,]  2.6665114486  0.340892670
##  [711,] -0.1712149691  0.638550652
##  [712,]  0.4357429537  1.176932174
##  [713,]  1.1577362191  0.317755836
##  [714,]  0.4665706407  0.472472613
##  [715,]  0.2739500748  1.701776680
##  [716,]  2.1558939634  0.821923743
##  [717,]  0.9864417016  0.588450817
##  [718,] -0.1548114038  0.978500856
##  [719,]  0.4338173904  8.139010844
##  [720,]  0.5845734277  0.151823914
##  [721,]  0.1066787577  0.463123077
##  [722,]  0.7359606455  0.713849807
##  [723,]  0.7931594039  0.020506267
##  [724,]  2.0826191826  0.196270856
##  [725,]  0.5390778237  1.496859595
##  [726,]  2.1587396627  0.522846208
##  [727,]  1.3372121741  0.234592515
##  [728,]  1.4504242879  1.206869508
##  [729,]  0.0883777856 -0.077940212
##  [730,]  1.4818751486  0.423612692
##  [731,]  1.1093294807  3.753922031
##  [732,]  0.1004706764  1.370347095
##  [733,]  1.0726967225  0.475501935
##  [734,] -0.0159355557  3.067301037
##  [735,]  0.2807731734 -0.036147534
##  [736,] -0.1745057029  2.559752606
##  [737,]  3.3282763668 -0.060865010
##  [738,]  0.0786294554  0.246082423
##  [739,]  0.2076049914  1.380073291
##  [740,]  0.4453255752  1.151374787
##  [741,]  1.2652472450  1.956447335
##  [742,]  2.8865205920  0.963656297
##  [743,]  0.3563837556  6.418380918
##  [744,]  1.1890241324  2.302888469
##  [745,]  0.0022513960  0.412681371
##  [746,]  0.3946369088 -0.252737462
##  [747,]  1.6978580641  0.790183779
##  [748,]  0.1085038493  0.067689131
##  [749,]  2.4774546063  0.877184640
##  [750,]  1.0194455535  0.443650015
##  [751,]  5.1512229559  3.976600377
##  [752,]  0.1255685319  1.463177991
##  [753,]  3.5526122096  0.537520055
##  [754,]  0.3415923213  0.540558771
##  [755,]  0.3240452393  1.735772637
##  [756,]  2.9291042519  0.101871125
##  [757,]  4.9008311557  3.045936070
##  [758,]  0.0542486228  0.041408707
##  [759,]  0.4900724740  2.129452334
##  [760,] -0.0182745014  0.690029991
##  [761,]  0.3569421866  0.275996534
##  [762,]  0.9966103648  0.597219363
##  [763,]  3.0251112797  1.691393828
##  [764,]  0.4849942400  0.078261491
##  [765,]  0.2677481520  1.462043794
##  [766,] -0.4030587934  1.729363981
##  [767,]  2.6794201252  0.591882178
##  [768,]  0.2836822974  0.853636993
##  [769,]  1.9701397698  1.327300457
##  [770,]  2.4394661816  0.472750028
##  [771,]  1.2046099342  0.509288911
##  [772,]  2.7947392521 -0.109486036
##  [773,]  2.7759363726 -0.293105143
##  [774,] -0.0357302120  0.096556271
##  [775,] -0.1018734314  1.031827149
##  [776,]  1.4598730227  3.132120604
##  [777,]  2.6388399615 -0.064222404
##  [778,] -0.2910828473  1.037401732
##  [779,]  1.0576755474  1.082297288
##  [780,]  0.0581371044  1.952565960
##  [781,]  0.4177976085 -0.148491961
##  [782,]  0.6460102264  0.437676087
##  [783,]  0.2828478674  0.741023333
##  [784,]  1.5485458561  0.126251536
##  [785,]  1.4347841142  0.477089684
##  [786,]  0.4988186903 -0.016685408
##  [787,]  1.5534458648  0.104453367
##  [788,] -0.0124976819 -0.101233586
##  [789,]  0.3750115425  2.413935382
##  [790,]  1.2343329280  0.792911281
##  [791,]  0.1692699352  2.173926742
##  [792,]  0.4028847038  0.975032968
##  [793,]  0.2771378253  0.274963344
##  [794,]  0.2325330317  0.765989246
##  [795,]  0.3751012752 -0.112582884
##  [796,]  0.3644075331  1.160137613
##  [797,]  0.2698766066  2.329435006
##  [798,]  2.6313364487  0.880469765
##  [799,]  0.2095287430  5.851488052
##  [800,]  0.2103946765  1.001996748
##  [801,]  0.6412429751  0.481757617
##  [802,]  1.9191357192  3.198050123
##  [803,]  1.6685903222  1.511310418
##  [804,]  0.3321925762  4.048305801
##  [805,]  0.9424821586  0.051309446
##  [806,]  0.1991158758 -0.004841911
##  [807,]  0.6533141790  0.335737507
##  [808,]  0.5087139095  0.489042616
##  [809,]  0.0365241283  2.277848005
##  [810,]  0.3257667716  0.844798877
##  [811,]  1.1070927795  0.945504324
##  [812,] -0.1345585190  2.716868296
##  [813,]  1.8974424466  2.057999319
##  [814,]  3.4785007311  0.636930095
##  [815,]  2.2391541370  4.185997552
##  [816,]  0.8267627368 -0.202842514
##  [817,] -0.2299026529  0.266225155
##  [818,]  0.5196673779  0.533826254
##  [819,]  0.0336446681  0.022013846
##  [820,]  0.2136450608  0.532539924
##  [821,]  0.9969363697  1.830542300
##  [822,]  0.5520974239  4.833531021
##  [823,]  0.3226452971  0.894002559
##  [824,]  1.2197786484  0.487676040
##  [825,] -0.0166869627  0.962636077
##  [826,] -0.1052274752  0.327606377
##  [827,]  1.0600567342  0.914697653
##  [828,]  0.6340094368  0.906339741
##  [829,]  1.0244131442  0.376404757
##  [830,]  2.8803966277  0.780930743
##  [831,] -0.3186308990  3.925111984
##  [832,]  0.8416583073  0.755608776
##  [833,]  2.4485812085  2.149284085
##  [834,]  1.0848855275 -0.184237519
##  [835,]  0.1500888289  1.499025027
##  [836,]  2.9740817902  1.438112273
##  [837,]  1.9205032499  0.757579346
##  [838,]  2.4328132874  0.809859732
##  [839,]  0.3243629701 -0.157204953
##  [840,]  2.9077321389 -0.236780288
##  [841,]  2.9135548404  0.160355012
##  [842,]  0.8143100977  1.641602943
##  [843,]  0.1161796578  0.054754122
##  [844,] -0.2576372201  4.687180445
##  [845,]  0.2066499798  1.564421837
##  [846,]  1.3737786598  0.455754853
##  [847,]  1.8602754564 -0.278441477
##  [848,]  1.1877224807  1.109120983
##  [849,] -0.2749925926  1.289861374
##  [850,]  2.1719869283  0.548049378
##  [851,]  0.0311335158  1.443001242
##  [852,]  1.9190048991  0.671241392
##  [853,]  1.9760375263  1.211025935
##  [854,]  3.0200189530  0.552194209
##  [855,]  0.3194231054  0.998936993
##  [856,]  0.3125369766  2.693485677
##  [857,]  3.1957675726  0.852063744
##  [858,]  2.3000843336  1.324582751
##  [859,]  0.4818089629  0.778767051
##  [860,]  0.8798237872  3.005648679
##  [861,]  0.2263098937  2.471589619
##  [862,]  0.2417144302  0.902273447
##  [863,] -0.0655476363  1.218584357
##  [864,]  1.7847285531 -0.159665149
##  [865,]  0.0471599045  0.163122154
##  [866,]  0.8596552747  0.298571672
##  [867,]  2.1242133466  1.330526594
##  [868,]  1.4823227974 -0.190681537
##  [869,]  0.2628252893  3.041132280
##  [870,]  0.6241788241 -0.140304429
##  [871,] -0.2523421002  0.640761497
##  [872,]  1.8667193724  0.767550895
##  [873,]  1.9827944130  2.351128118
##  [874,]  0.4364427348  0.753138551
##  [875,] -0.0778379440  0.186609268
##  [876,]  2.0169381685  0.232212526
##  [877,] -0.2628504833  0.051916295
##  [878,]  0.4145746778  0.833550167
##  [879,]  0.8053700305  0.052815295
##  [880,]  0.2572838033  1.376850972
##  [881,]  1.1760205628 -0.094355383
##  [882,]  1.4066968386  1.123415286
##  [883,] -0.1288515725  3.122912318
##  [884,]  0.7122703780  0.132387361
##  [885,]  3.8848092018  0.947768223
##  [886,]  0.6540975277  0.520864340
##  [887,]  2.6205380493  0.797612800
##  [888,]  0.7042258727  1.159796099
##  [889,]  0.3957904116  0.303155405
##  [890,]  0.0636852388 -0.171417291
##  [891,]  2.0669337918 -0.146858850
##  [892,]  0.1102113676 -0.250560128
##  [893,]  2.8215446375  0.765378419
##  [894,]  0.7266353723  2.704084956
##  [895,]  2.0236857016  0.406396366
##  [896,]  0.5767084678  1.415193371
##  [897,]  0.6030039948 -0.001908206
##  [898,]  5.2838148471  3.451443678
##  [899,]  0.0729013262  0.669796735
##  [900,]  0.8213443761  0.188597470
##  [901,] -0.3262932995  1.215918777
##  [902,]  0.2870888580  0.243571525
##  [903,]  1.8591853313  2.453750808
##  [904,]  1.8963306703  1.154836301
##  [905,]  0.0380042131  1.281540592
##  [906,]  0.4196498163  0.324187772
##  [907,]  0.9731615797  2.100239419
##  [908,]  1.0328296922  0.257511980
##  [909,]  2.9663071236  0.616500731
##  [910,]  0.5546955749  1.822032849
##  [911,] -0.0553016672  0.583984812
##  [912,]  1.3800093969  0.187232216
##  [913,]  1.6813360977  0.457989461
##  [914,]  2.3471992698  1.259808964
##  [915,]  0.3218683947  2.855545999
##  [916,]  2.7118654680  0.813195636
##  [917,]  2.3585106863  1.152102697
##  [918,]  2.5907293820  2.371054248
##  [919,]  0.3036050624  1.319933730
##  [920,]  0.4271359537  0.002995628
##  [921,]  0.4242711659  2.026414320
##  [922,]  1.0654576321  0.679857611
##  [923,]  1.7711905985  0.516563779
##  [924,]  0.5978366311  4.503201670
##  [925,]  0.5191338120  0.974215747
##  [926,] 13.3916782943 -0.079187511
##  [927,]  2.9206745329 -0.035192100
##  [928,]  2.5618845735  0.284313156
##  [929,]  0.2977123530  0.193009727
##  [930,]  2.9839684256  2.160921187
##  [931,]  0.7364351556  2.722220100
##  [932,]  0.4060467393  1.552907806
##  [933,]  1.5803861103  2.541710870
##  [934,]  0.3875621723  3.039902234
##  [935,]  0.6731454887  3.323428626
##  [936,]  2.7873234515  1.983347882
##  [937,]  0.4102602934  2.385422829
##  [938,] -0.1181172916  0.324337843
##  [939,]  3.3509704004 -0.096167668
##  [940,]  0.3691980839  0.309466038
##  [941,]  0.3598752621  0.749909920
##  [942,]  1.5123128923  0.171029016
##  [943,]  0.0091500736  1.272607849
##  [944,] -0.0987595486  0.626654926
##  [945,]  0.1216604021  1.066659906
##  [946,]  0.9477447074  0.527163579
##  [947,]  1.4575926081  1.084193509
##  [948,]  0.5559553770  0.242472788
##  [949,]  2.1168721084  1.047687619
##  [950,]  0.2569539473  0.829226054
##  [951,]  0.3147368927  0.348493891
##  [952,]  0.7808350229 -0.212736147
##  [953,]  2.1461503389 -0.015433735
##  [954,]  1.2817746538  0.122724743
##  [955,]  0.2304499125  2.112342440
##  [956,]  1.9670305671  1.339623969
##  [957,]  1.1817900361  1.958412866
##  [958,]  0.1913889326  0.936762027
##  [959,]  0.4029531692 -0.202435530
##  [960,]  0.7681921706  0.125969106
##  [961,]  0.3067518914  0.548691189
##  [962,]  0.4406931046  0.495322894
##  [963,]  0.8782210114  0.382258716
##  [964,]  0.2158108994  2.478298039
##  [965,]  0.4455268900  0.792881219
##  [966,]  0.3280753721  1.927580303
##  [967,]  1.4996539213 -0.292105560
##  [968,]  4.0182794385  4.905235287
##  [969,]  0.3693551093  0.628189303
##  [970,]  0.0297575121  1.784198139
##  [971,]  0.9184103346  4.045041845
##  [972,]  0.0899180282  1.191004808
##  [973,]  0.8212161259 -0.081708949
##  [974,]  3.6627517004  0.672799038
##  [975,]  1.3322169209  0.612296017
##  [976,]  0.0835673940  0.627223279
##  [977,]  0.4391566444  0.210612498
##  [978,]  1.3975443924  0.501346153
##  [979,]  0.5200186388  1.097218328
##  [980,]  0.3865665333  0.746815093
##  [981,]  1.9374761507  1.179040504
##  [982,]  1.4078087568  0.328575441
##  [983,]  2.6983742808  2.547225766
##  [984,]  0.8095081206  2.800580804
##  [985,]  0.6640327044  0.118065791
##  [986,]  0.5581794008  2.417895739
##  [987,]  0.8641493265  3.037314825
##  [988,]  0.2551565187  0.865663778
##  [989,] -0.2104561120  0.376667709
##  [990,]  2.9188440025  0.895658289
##  [991,] -0.0137243973  0.323714279
##  [992,]  0.5194672214  0.622105908
##  [993,]  0.2304670501 -0.036684999
##  [994,]  0.3006070909  0.646242590
##  [995,]  3.0432435015  6.650730940
##  [996,]  4.7231363582  2.352871762
##  [997,]  3.5409136137  1.473905831
##  [998,]  0.8601022134  1.875417900
##  [999,]  0.0254516771  0.211900011
## 
## $model.matrix
##    (Intercept) avlength avcondition   T_av O2_sat_av    Con_av COD_av NH4._av
## 1            1 46.26316   0.7032430 11.114    81.286  740.7140 13.333   0.158
## 2            1 38.30000   0.6196317 10.440    65.400  609.6000  1.400   0.774
## 3            1 47.20000   0.7209293 12.858    75.333  434.7500 25.917   2.251
## 4            1 33.60000   0.7279046 13.086    72.857  949.0000 25.000   5.000
## 5            1 33.30769   0.6910252 11.750    96.833  896.1670 14.000   0.303
## 6            1 35.05263   0.7161573 13.557    84.571  340.7140 29.000   0.252
## 7            1 35.53333   0.7532778 11.750    88.417  716.3330 16.583   0.393
## 9            1 41.66667   0.8590551 12.008    87.000  800.3330 21.917   0.468
## 11           1 39.89474   0.6943120 13.550    63.167  527.6670 45.500   3.233
## 12           1 32.90909   0.6629259 14.957    65.857 1089.8570 50.500   5.365
## 13           1 39.88235   0.7324076 14.486    90.429  771.7143 11.333   0.668
## 14           1 38.42857   0.7578120 11.983    77.667  472.3330 37.167   2.367
## 15           1 34.23077   0.7642545 11.577    85.308  591.4620 24.667   0.260
## 16           1 43.61111   0.6500428 12.443    87.857  462.5710 37.167   0.210
## 17           1 40.16667   0.7486984 11.425    73.250  470.3330 20.000   2.589
## 18           1 37.43750   0.9549238 16.214    61.000  422.4290 35.833   2.417
## 19           1 41.47059   0.6295888  9.317    94.900  812.8330  7.500   0.103
## 20           1 28.00000   0.7382850 12.957    85.571  851.2860 15.833   0.170
## 21           1 37.84211   0.7477438 15.000    85.333  673.1670 19.500   0.635
## 22           1 42.00000   0.6865490 10.475    73.833  255.8330 24.727   0.527
## 23           1 36.50000   0.7425513 10.050    80.000  138.6670 37.167   0.290
## 24           1 43.58333   0.8243429 11.773    66.091  593.0910 34.727   0.806
## 26           1 31.72222   0.8809334 12.167    80.333  897.4170 16.417   0.409
## 28           1 40.31579   0.7644699 13.433    99.667  801.0000 20.909   0.354
## 29           1 39.25000   0.8383703 14.133    87.667  669.6670 14.000   0.227
## 30           1 42.37500   0.7907723 13.542    48.833  542.4170 42.333   2.261
## 31           1 42.00000   0.8148913 12.867    70.333  447.3330 29.333   0.680
## 32           1 38.87500   0.6351264 13.186    91.857  617.5710 19.333   0.362
## 33           1 37.31579   0.7512399 15.233    84.000  539.3330 13.667   0.325
## 34           1 38.73684   0.6217274 12.050    92.583  659.8330 14.750   0.336
## 35           1 37.85714   0.8194431 11.175    91.375  687.3750 26.000   0.395
## 36           1 32.88889   0.6862546 13.700    88.833  755.5000 26.167   1.260
## 38           1 34.65000   0.6616806 13.633    77.500  667.0000 20.333   0.695
## 39           1 33.25000   0.7554143 11.333    43.750  848.3330 35.750   2.542
## 40           1 36.75000   0.6487052 12.900    71.400  635.0000 16.400   2.208
## 41           1 36.35000   0.8265861 15.100    94.000  716.3330 15.167   0.165
## 42           1 35.15789   0.7600249 13.786    89.571  705.7140 18.167   0.880
##        Nt_av pool_riffle1 meander1   netcen    updist
## 1   8.917000           -1       -1 65212.97 67745.125
## 2   4.780000            1        1 50877.11 52437.119
## 3   8.925000            1       -1 38651.53 32574.449
## 4   9.067000           -1       -1 63911.70 65226.644
## 5   5.167000            1       -1 64168.17 67952.655
## 6   1.617000            1        1 45262.05 45780.074
## 7   2.775000            1        1 72386.11 76509.324
## 9   6.083000            1       -1 47724.46 49932.683
## 11  5.750000            1        1 49875.30 52217.733
## 12 16.100000           -1       -1 61880.37 26695.488
## 13  6.533000            1        1 60618.70 25511.682
## 14  7.000000            1        1 56056.62 15064.968
## 15  2.608000           -1        1 63687.75 67470.687
## 16  1.730000           -1       -1 68548.11 72561.660
## 17 10.617000           -1       -1 45271.82 39387.485
## 18  5.450000            1       -1 44142.92 15837.759
## 19  5.358361           -1       -1 64632.42 67396.486
## 20  4.583000            1       -1 72865.43 76898.411
## 21  5.067000           -1        1 58440.64 21751.460
## 22  2.164000            1        1 47879.02 44196.470
## 23  1.372000            1        1 53511.26 49989.625
## 24  4.891000            1       -1 37413.39 35027.425
## 26  5.242000            1        1 59347.24 62693.461
## 28  4.636000            1       -1 45740.16 46890.918
## 29  7.550000           -1       -1 73590.70 39137.994
## 30  3.317000            1        1 45131.08 29684.138
## 31  3.283000            1        1 43713.21  2368.891
## 32  4.767000           -1       -1 55885.32 18797.654
## 33  3.683000            1        1 63398.00 26850.462
## 34  8.050000           -1        1 65158.98 30465.362
## 35  4.317000           -1       -1 59901.23 62281.614
## 36  5.567000           -1        1 63856.37 66416.408
## 38  7.033000            1        1 53189.12 16286.394
## 39  5.017000            1        1 63663.04 23736.389
## 40  3.243000            1        1 60384.21 20784.664
## 41  2.550000           -1       -1 60481.19 20943.659
## 42  3.450000            1        1 64836.74 25423.656
## 
## $terms
## meandist_bray ~ avlength + avcondition + T_av + O2_sat_av + Con_av + 
##     COD_av + NH4._av + Nt_av + pool_riffle + meander + netcen + 
##     updist
## attr(,"variables")
## list(meandist_bray, avlength, avcondition, T_av, O2_sat_av, Con_av, 
##     COD_av, NH4._av, Nt_av, pool_riffle, meander, netcen, updist)
## attr(,"factors")
##               avlength avcondition T_av O2_sat_av Con_av COD_av NH4._av Nt_av
## meandist_bray        0           0    0         0      0      0       0     0
## avlength             1           0    0         0      0      0       0     0
## avcondition          0           1    0         0      0      0       0     0
## T_av                 0           0    1         0      0      0       0     0
## O2_sat_av            0           0    0         1      0      0       0     0
## Con_av               0           0    0         0      1      0       0     0
## COD_av               0           0    0         0      0      1       0     0
## NH4._av              0           0    0         0      0      0       1     0
## Nt_av                0           0    0         0      0      0       0     1
## pool_riffle          0           0    0         0      0      0       0     0
## meander              0           0    0         0      0      0       0     0
## netcen               0           0    0         0      0      0       0     0
## updist               0           0    0         0      0      0       0     0
##               pool_riffle meander netcen updist
## meandist_bray           0       0      0      0
## avlength                0       0      0      0
## avcondition             0       0      0      0
## T_av                    0       0      0      0
## O2_sat_av               0       0      0      0
## Con_av                  0       0      0      0
## COD_av                  0       0      0      0
## NH4._av                 0       0      0      0
## Nt_av                   0       0      0      0
## pool_riffle             1       0      0      0
## meander                 0       1      0      0
## netcen                  0       0      1      0
## updist                  0       0      0      1
## attr(,"term.labels")
##  [1] "avlength"    "avcondition" "T_av"        "O2_sat_av"   "Con_av"     
##  [6] "COD_av"      "NH4._av"     "Nt_av"       "pool_riffle" "meander"    
## [11] "netcen"      "updist"     
## attr(,"order")
##  [1] 1 1 1 1 1 1 1 1 1 1 1 1
## attr(,"intercept")
## [1] 1
## attr(,"response")
## [1] 1
## attr(,".Environment")
## <environment: R_GlobalEnv>
## 
## attr(,"class")
## [1] "adonis"
# environmental variables
env_select <- environment2[,c("T_av", "O2_sat_av", "Con_av", "COD_av", "NH4._av", "Nt_av", "pool_riffle", "meander", "netcen", "updist")]
env_select$pool_riffle <- as.numeric(env_select$pool_riffle)
env_select$meander <- as.numeric(env_select$meander)

pca <- prcomp(env_select, scale.=T)
summary(pca)
## Importance of components:
##                           PC1    PC2    PC3    PC4     PC5     PC6     PC7
## Standard deviation     1.7124 1.5545 1.1221 1.0140 0.88807 0.79463 0.56647
## Proportion of Variance 0.2933 0.2416 0.1259 0.1028 0.07887 0.06314 0.03209
## Cumulative Proportion  0.2933 0.5349 0.6608 0.7636 0.84248 0.90563 0.93771
##                            PC8     PC9    PC10
## Standard deviation     0.50483 0.46939 0.38429
## Proportion of Variance 0.02549 0.02203 0.01477
## Cumulative Proportion  0.96320 0.98523 1.00000
plot(pca)

biplot(pca)

8.2.1 Effect of environment on infracommunity structure

# Assess the effect of environmental variables on parasite infracommunity dissimilarities using distance based RDA
spe.rda <- dbrda(meandist_bray ~ T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
anova(spe.rda)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander, data = env_select)
##          Df SumOfSqs      F Pr(>F)   
## Model     8  0.45036 1.3833   0.01 **
## Residual 28  1.13946                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RsquareAdj(spe.rda)$adj.r.squared
## [1] 0.07850103
mod0 <- dbrda(meandist_bray ~ 1, env_select)  # Model with intercept only  #edit_PH
mod1 <- dbrda(meandist_bray ~ ., env_select)  # Model with all explanatory variables  #edit_PH
step.res <- ordiR2step(mod0, mod1, direction = "both",perm.max = 200)
## Step: R2.adj= 0 
## Call: meandist_bray ~ 1 
##  
##                   R2.adjusted
## <All variables>  0.0898822750
## + Con_av         0.0492715387
## + NH4._av        0.0376899022
## + Nt_av          0.0353578268
## + COD_av         0.0097867139
## + updist         0.0092890919
## + pool_riffle    0.0070398050
## + netcen         0.0034499960
## + O2_sat_av      0.0031240320
## <none>           0.0000000000
## + T_av          -0.0005031246
## + meander       -0.0037253892
## 
##          Df    AIC      F Pr(>F)   
## + Con_av  1 17.228 2.8657  0.002 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Step: R2.adj= 0.04927154 
## Call: meandist_bray ~ Con_av 
##  
##                 R2.adjusted
## <All variables>  0.08988227
## + COD_av         0.08426096
## + NH4._av        0.07058808
## + updist         0.06800179
## + O2_sat_av      0.06266812
## + netcen         0.05455352
## + meander        0.05428744
## + Nt_av          0.05273614
## <none>           0.04927154
## + pool_riffle    0.04923534
## + T_av           0.04694754
## 
##          Df    AIC      F Pr(>F)   
## + COD_av  1 16.768 2.3373  0.002 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Step: R2.adj= 0.08426096 
## Call: meandist_bray ~ Con_av + COD_av 
##  
##                 R2.adjusted
## + updist         0.09961037
## + meander        0.09248673
## <All variables>  0.08988227
## + netcen         0.08626581
## + pool_riffle    0.08559576
## <none>           0.08426096
## + T_av           0.08115910
## + O2_sat_av      0.08092067
## + Nt_av          0.07979657
## + NH4._av        0.07591794
step.res$anova  # Summary table
##                   R2.adj Df    AIC      F Pr(>F)   
## + Con_av        0.049272  1 17.228 2.8657  0.002 **
## + COD_av        0.084261  1 16.768 2.3373  0.002 **
## <All variables> 0.089882                           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
spe.rda <- dbrda(meandist_bray ~  Con_av + COD_av, env_select)
plot(spe.rda, scaling = 1) # it is for technical reasons not possible to plot both site and species scores

summary(spe.rda)
## 
## Call:
## dbrda(formula = meandist_bray ~ Con_av + COD_av, data = env_select) 
## 
## Partitioning of squared Unknown distance:
##               Inertia Proportion
## Total          1.5898     1.0000
## Constrained    0.2148     0.1351
## Unconstrained  1.3750     0.8649
## 
## Eigenvalues, and their contribution to the squared Unknown distance 
## 
## Importance of components:
##                       dbRDA1  dbRDA2   MDS1    MDS2   MDS3    MDS4    MDS5
## Eigenvalue            0.1863 0.02858 0.1972 0.15873 0.1207 0.08661 0.07076
## Proportion Explained  0.1172 0.01798 0.1240 0.09984 0.0759 0.05447 0.04451
## Cumulative Proportion     NA      NA     NA      NA     NA      NA      NA
##                          MDS6    MDS7    MDS8    MDS9   MDS10   MDS11   MDS12
## Eigenvalue            0.06231 0.04802 0.04613 0.04387 0.04231 0.03826 0.03703
## Proportion Explained  0.03919 0.03021 0.02901 0.02760 0.02661 0.02406 0.02329
## Cumulative Proportion      NA      NA      NA      NA      NA      NA      NA
##                         MDS13   MDS14   MDS15   MDS16   MDS17   MDS18   MDS19
## Eigenvalue            0.03557 0.03355 0.03200 0.02808 0.02797 0.02575 0.02487
## Proportion Explained  0.02237 0.02110 0.02013 0.01766 0.01759 0.01620 0.01564
## Cumulative Proportion      NA      NA      NA      NA      NA      NA      NA
##                         MDS20   MDS21   MDS22   MDS23   MDS24   MDS25   MDS26
## Eigenvalue            0.02377 0.02238 0.02182 0.02104 0.01990 0.01880 0.01782
## Proportion Explained  0.01495 0.01408 0.01372 0.01323 0.01252 0.01183 0.01121
## Cumulative Proportion      NA      NA      NA      NA      NA      NA      NA
##                         MDS27   MDS28    MDS29    MDS30    MDS31    MDS32
## Eigenvalue            0.01719 0.01622 0.011778 0.010499 0.007903 0.006958
## Proportion Explained  0.01081 0.01020 0.007408 0.006604 0.004971 0.004376
## Cumulative Proportion      NA      NA       NA       NA       NA       NA
##                          MDS33     iMDS1
## Eigenvalue            0.005670 -0.006426
## Proportion Explained  0.003566  0.004042
## Cumulative Proportion       NA        NA
## 
## Accumulated constrained eigenvalues
## Importance of components:
##                       dbRDA1  dbRDA2
## Eigenvalue            0.1863 0.02858
## Proportion Explained  0.8670 0.13304
## Cumulative Proportion 0.8670 1.00000
## 
## Scaling 2 for species and site scores
## * Species are scaled proportional to eigenvalues
## * Sites are unscaled: weighted dispersion equal on all dimensions
## * General scaling constant of scores:  2.750505 
## 
## 
## Site scores (weighted sums of species scores)
## 
##            dbRDA1   dbRDA2     MDS1     MDS2     MDS3      MDS4
## SITE 1  -0.215744 -0.44381  0.01302  0.31819 -0.28116 -0.178171
## SITE 11 -0.507248 -0.82144 -0.09719 -0.28198 -0.04679  0.342258
## SITE 12 -0.746029 -0.15775  0.31672  0.25334 -0.08234 -0.151368
## SITE 13 -0.005847  0.21986 -0.02027  0.91847 -0.12233 -0.332031
## SITE 14 -0.101987 -0.28502  0.01314  0.55873 -0.09066 -0.223950
## SITE 15 -0.290401  0.51714 -0.23614 -0.10408 -0.36670 -0.263022
## SITE 16  0.016467 -0.22318  0.14693 -0.09879 -0.21010  0.156923
## SITE 17 -0.053594 -0.78979  0.68552  0.22623  0.55763  0.068555
## SITE 18  0.741297  0.34140  0.34156 -0.78781 -0.33039  0.372025
## SITE 19  2.204147 -0.31903  0.07576 -0.77176 -0.32619  0.237586
## SITE 2  -0.334822 -0.53901  0.20181  0.23760  0.25255  0.460075
## SITE 20  0.132501  1.43824 -0.36307 -0.15683  0.91526  0.652586
## SITE 21 -0.518164 -0.15765  0.51672  0.22690 -0.05180  0.071838
## SITE 22 -0.681351  0.71637  0.44536  0.61813  0.24285 -0.440713
## SITE 23  0.085803  0.07384 -0.18742 -0.58764 -0.50280  0.146049
## SITE 24 -0.506368  1.41199 -0.02580  0.53865  0.25884  0.040947
## SITE 26  0.017028 -0.61108  0.37526 -0.36715 -0.10492  0.425754
## SITE 28  0.121498 -0.47609  0.59944 -0.22080 -0.07107  0.465237
## SITE 29 -0.014961 -0.35365  0.04914 -0.10076 -0.08378  0.641604
## SITE 3  -0.711132  0.09645  0.08469 -0.08718 -0.21517  0.038217
## SITE 30 -0.812113  0.12175  0.55582 -0.16918 -0.25866  0.087617
## SITE 31  0.043616  0.61571 -0.31459  0.47663 -0.16031 -0.651535
## SITE 32  0.562390 -0.35603 -0.38737  0.06837 -0.20621 -0.072343
## SITE 33 -0.372173 -0.03501  0.10319  0.85337 -0.01445 -0.328696
## SITE 34 -0.466651 -0.48378  0.50738  0.02349 -0.08407  0.306511
## SITE 35  0.163917  1.66724 -0.04520  0.22652  0.57157  0.198776
## SITE 36 -0.296043  0.76361 -0.59812  0.40106 -0.04152 -0.249681
## SITE 38  0.302702 -0.34509 -0.16274 -0.49724 -0.25040 -0.005416
## SITE 39 -0.978171 -0.31142  0.36167  0.40699  0.02355  0.020399
## SITE 4  -0.141634 -0.44343 -0.02774 -0.11080 -0.07834  0.180628
## SITE 40  0.496377  0.01681 -0.38350 -0.04028 -0.50240 -0.167352
## SITE 41  1.117637 -0.21808 -0.82799 -0.60061 -0.49878 -0.637014
## SITE 42  0.437517  0.97421 -1.46550  0.08641  1.33505  0.880493
## SITE 5   0.522987 -0.17736  0.27513  0.18757 -0.04206  0.152978
## SITE 6   0.423826  0.07352 -0.91744 -0.10155 -0.42928 -0.789691
## SITE 7   0.013170 -1.17661  0.57227 -1.15454  1.52741 -1.616432
## SITE 9   0.351552 -0.32386 -0.18044 -0.38769 -0.23204  0.160360
## 
## 
## Site constraints (linear combinations of constraining variables)
## 
##            dbRDA1   dbRDA2     MDS1     MDS2     MDS3      MDS4
## SITE 1  -0.079483 -0.44275  0.01302  0.31819 -0.28116 -0.178171
## SITE 11 -0.692558 -0.69501 -0.09719 -0.28198 -0.04679  0.342258
## SITE 12 -0.387516  0.29270  0.31672  0.25334 -0.08234 -0.151368
## SITE 13  0.692033 -0.28074 -0.02027  0.91847 -0.12233 -0.332031
## SITE 14  0.273072 -0.58517  0.01314  0.55873 -0.09066 -0.223950
## SITE 15 -0.503973  0.49304 -0.23614 -0.10408 -0.36670 -0.263022
## SITE 16 -0.041630 -0.31054  0.14693 -0.09879 -0.21010  0.156923
## SITE 17  0.286975 -0.22462  0.68552  0.22623  0.55763  0.068555
## SITE 18  0.355899  0.83587  0.34156 -0.78781 -0.33039  0.372025
## SITE 19  1.702755  0.40556  0.07576 -0.77176 -0.32619  0.237586
## SITE 2  -0.068404 -0.54101  0.20181  0.23760  0.25255  0.460075
## SITE 20  0.005618  0.62143 -0.36307 -0.15683  0.91526  0.652586
## SITE 21 -0.085484  0.08616  0.51672  0.22690 -0.05180  0.071838
## SITE 22 -0.015359  0.63175  0.44536  0.61813  0.24285 -0.440713
## SITE 23 -0.475351  0.06131 -0.18742 -0.58764 -0.50280  0.146049
## SITE 24 -0.138656  0.63048 -0.02580  0.53865  0.25884  0.040947
## SITE 26 -0.086478 -0.70999  0.37526 -0.36715 -0.10492  0.425754
## SITE 28  0.227529 -0.47771  0.59944 -0.22080 -0.07107  0.465237
## SITE 29 -0.053389 -0.16940  0.04914 -0.10076 -0.08378  0.641604
## SITE 3  -0.805011  0.44279  0.08469 -0.08718 -0.21517  0.038217
## SITE 30 -0.711357  0.97402  0.55582 -0.16918 -0.25866  0.087617
## SITE 31  0.197349  0.41392 -0.31459  0.47663 -0.16031 -0.651535
## SITE 32  0.342870 -0.50733 -0.38737  0.06837 -0.20621 -0.072343
## SITE 33  0.260419 -0.25833  0.10319  0.85337 -0.01445 -0.328696
## SITE 34 -0.213627 -0.34583  0.50738  0.02349 -0.08407  0.306511
## SITE 35  0.299656  0.71657 -0.04520  0.22652  0.57157  0.198776
## SITE 36 -0.265626  0.39128 -0.59812  0.40106 -0.04152 -0.249681
## SITE 38 -0.177490 -0.11612 -0.16274 -0.49724 -0.25040 -0.005416
## SITE 39 -0.502932 -0.21901  0.36167  0.40699  0.02355  0.020399
## SITE 4  -0.213933 -0.31087 -0.02774 -0.11080 -0.07834  0.180628
## SITE 40  0.157625  0.02847 -0.38350 -0.04028 -0.50240 -0.167352
## SITE 41  0.308647 -0.03805 -0.82799 -0.60061 -0.49878 -0.637014
## SITE 42 -0.043511 -0.13560 -1.46550  0.08641  1.33505  0.880493
## SITE 5   0.774214  0.17770  0.27513  0.18757 -0.04206  0.152978
## SITE 6  -0.221478 -0.23059 -0.91744 -0.10155 -0.42928 -0.789691
## SITE 7  -0.080948 -0.35692  0.57227 -1.15454  1.52741 -1.616432
## SITE 9  -0.020466 -0.24745 -0.18044 -0.38769 -0.23204  0.160360
## 
## 
## Biplot scores for constraining variables
## 
##        dbRDA1  dbRDA2 MDS1 MDS2 MDS3 MDS4
## Con_av 0.7628 -0.6467    0    0    0    0
## COD_av 0.4413  0.8974    0    0    0    0
anova(spe.rda)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ Con_av + COD_av, data = env_select)
##          Df SumOfSqs      F Pr(>F)    
## Model     2  0.21484 2.6563  0.001 ***
## Residual 34  1.37498                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
anova(spe.rda, by="term")
## Permutation test for dbrda under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ Con_av + COD_av, data = env_select)
##          Df SumOfSqs      F Pr(>F)   
## Con_av    1  0.12032 2.9752  0.002 **
## COD_av    1  0.09452 2.3373  0.009 **
## Residual 34  1.37498                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

8.2.2 Effect of space on infracommunity structure

spe.rda <- dbrda(meandist_bray ~ netcen + updist, data = env_select)
anova(spe.rda)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ netcen + updist, data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     2  0.10742 1.2319  0.163
## Residual 34  1.48240
RsquareAdj(spe.rda)$adj.r.squared
## [1] 0.01271734
anova.cca(spe.rda, step=1000);
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ netcen + updist, data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     2  0.10742 1.2319  0.138
## Residual 34  1.48240
anova.cca(spe.rda, step=1000, by="term");
## Permutation test for dbrda under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ netcen + updist, data = env_select)
##          Df SumOfSqs      F Pr(>F)
## netcen    1  0.04949 1.1352  0.267
## updist    1  0.05792 1.3285  0.125
## Residual 34  1.48240
RsquareAdj(spe.rda)$adj.r.squared;
## [1] 0.01271734
RsquareAdj(spe.rda)$r.squared
## [1] 0.06756637

8.2.3 Variation partitioning

#Variation partitioning
spe.varpart1 <- varpart(meandist_bray, env_select[,1:8], env_select[,9:10])
plot(spe.varpart1,digits=2)

spe.varpart1
## 
## Partition of squared Unknown user-supplied distance in dbRDA 
## 
## Call: varpart(Y = meandist_bray, X = env_select[, 1:8], env_select[,
## 9:10])
## 
## Explanatory tables:
## X1:  env_select[, 1:8]
## X2:  env_select[, 9:10] 
## 
## No. of explanatory tables: 2 
## Total variation (SS): 1.5898 
## No. of observations: 37 
## 
## Partition table:
##                      Df R.squared Adj.R.squared Testable
## [a+c] = X1            8   0.28328       0.07850     TRUE
## [b+c] = X2            2   0.06757       0.01272     TRUE
## [a+b+c] = X1+X2      10   0.34269       0.08988     TRUE
## Individual fractions                                    
## [a] = X1|X2           8                 0.07716     TRUE
## [b] = X2|X1           2                 0.01138     TRUE
## [c]                   0                 0.00134    FALSE
## [d] = Residuals                         0.91012    FALSE
## ---
## Use function 'dbrda' to test significance of fractions of interest
anova.cca(dbrda(meandist_bray ~ T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander + Condition(netcen + updist),
                data=env_select), step=1000)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander + Condition(netcen + updist), data = env_select)
##          Df SumOfSqs      F Pr(>F)  
## Model     8   0.4374 1.3603  0.015 *
## Residual 26   1.0450                
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
anova.cca(dbrda(meandist_bray ~ netcen + updist+
                  Condition(T_av + O2_sat_av + Con_av + COD_av 
                     + NH4._av + Nt_av + pool_riffle + meander), data=env_select), step=1000)
## Permutation test for dbrda under reduced model
## Permutation: free
## Number of permutations: 999
## 
## Model: dbrda(formula = meandist_bray ~ netcen + updist + Condition(T_av + O2_sat_av + Con_av + COD_av + NH4._av + Nt_av + pool_riffle + meander), data = env_select)
##          Df SumOfSqs      F Pr(>F)
## Model     2  0.09446 1.1751  0.172
## Residual 26  1.04500